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1
Egloff, Daniel, Markus Leippold, and Liuren Wu. "The Term Structure of Variance Swap Rates and Optimal Variance Swap Investments." Journal of Financial and Quantitative Analysis 45, no. 5 (2010): 1279–310. http://dx.doi.org/10.1017/s0022109010000463.
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AbstractThis paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies 2 stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market price of variance risk makes it optimal for an investor to take short positions in a short-term variance swap contract, long positions in a long-term variance swap contract, and short positions in the stock index.
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Zeng, Z. B., and C. C. Cockerham. "Variance of neutral genetic variances within and between populations for a quantitative character." Genetics 129, no. 2 (1991): 535–53. http://dx.doi.org/10.1093/genetics/129.2.535.
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Abstract The variances of genetic variances within and between finite populations were systematically studied using a general multiple allele model with mutation in terms of identity by descent measures. We partitioned the genetic variances into components corresponding to genetic variances and covariances within and between loci. We also analyzed the sampling variance. Both transient and equilibrium results were derived exactly and the results can be used in diverse applications. For the genetic variance within populations, sigma 2 omega, the coefficient of variation can be very well approximated as [formula: see text] for a normal distribution of allelic effects, ignoring recurrent mutation in the absence of linkage, where m is the number of loci, N is the effective population size, theta 1(0) is the initial identity by descent measure of two genes within populations and t is the generation number. The first term is due to genic variance, the second due to linkage disequilibrium, and third due to sampling. In the short term, the variation is predominantly due to linkage disequilibrium and sampling; but in the long term it can be largely due to genic variance. At equilibrium with mutation [formula: see text] where u is the mutation rate. The genetic variance between populations is a parameter. Variance arises only among sample estimates due to finite sampling of populations and individuals. The coefficient of variation for sample gentic variance between populations, sigma 2b, can be generally approximated as [formula: see text] when the number of loci is large where S is the number of sampling populations.
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ZHU, YINGZI, and JIN E. ZHANG. "VARIANCE TERM STRUCTURE AND VIX FUTURES PRICING." International Journal of Theoretical and Applied Finance 10, no. 01 (2007): 111–27. http://dx.doi.org/10.1142/s0219024907004123.
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Using no arbitrage principle, we derive a relation between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.
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Wan, Fei. "Analyzing pre-post designs using the analysis of covariance models with and without the interaction term in a heterogeneous study population." Statistical Methods in Medical Research 29, no. 1 (2019): 189–204. http://dx.doi.org/10.1177/0962280219827971.
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Pre-post parallel group randomized designs have been frequently used to compare the effectiveness of competing treatment strategies and the ordinary least squares (OLS)-based analysis of covariance model (ANCOVA) is a routine analytic approach. In many scenarios, the associations between the baseline and the post-randomization scores could differ between the treatment and control arms, which justifies the inclusion of the treatment by baseline score interaction in ANCOVA. This heterogeneity may also cause heteroscedastic errors in ANCOVA. In this study, we compared the performances of the ANCOVA models with and without the interaction term in estimating the marginal treatment effect in a heterogeneous two-arm pre-post design. We explored the relationship between the two nested ANCOVA models from the perspective of an omitted variable bias problem and further revealed the reasons why the usual ANCOVA may fail in heterogeneous scenario through the discussion of the three types of variances associated with the ANCOVA estimators of the marginal treatment effect: the target unconditional variance, the conditional variance allowing unequal error variances, and the OLS conditional variance derived under the assumption of constant error variance. We demonstrated analytically and with simulations that the proposed heteroscadastic-consistent variance estimators provide valid unconditional inference for ANCOVA, and the ANCOVA interaction model is more powerful than the ANCOVA main effect model when a design is unbalanced.
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Fang, Ming, Richard J. Doviak, and Bruce A. Albrecht. "Significance of the Coupled Term in the Doppler Weather Radar Spectrum Width Equation." Journal of Atmospheric and Oceanic Technology 28, no. 4 (2011): 539–47. http://dx.doi.org/10.1175/2011jtecha1442.1.
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Abstract There is an additional zero mean random variable term that couples mean wind shear and turbulence in the Doppler radar spectrum width equation. This random variable, labeled the “coupled term,” has been neglected heretofore in the literature. Herein, the variance of the squared spectrum width ascribed to this coupled term is determined from data collected with a Weather Surveillance Radar-1988 Doppler (WSR-88D) in two snowstorms; it can exceed 1 m4 s−4. Thus, this coupled term can be a significant contributor to the variance of the spectrum width and must be considered when using spectrum width to deduce turbulence.
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Carboni, Giacomo. "TERM PREMIA IMPLICATIONS OF MACROECONOMIC REGIME CHANGES." Macroeconomic Dynamics 20, no. 1 (2014): 251–75. http://dx.doi.org/10.1017/s1365100514000352.
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Term premia are shown to provide crucial information for discriminating among alternative sources of change in the economy, namely shifts in the variance of structural shocks and in monetary policy. These sources have been identified as competing explanations for time-varying features of major industrial economies during the 1980s and 1990s. Although hardly distinguishable through the lens of standard dynamic stochastic general equilibrium (DSGE) models, lower nonpolicy shock variances and “tighter” monetary policy regimes imply higher and lower term premia, respectively. As a result, moving to tighter monetary policy alone cannot explain the improved U.S. macroeconomic stability in the 1980s and 1990s: term premia would have shifted downward, a fact inconsistent with the evidence of higher premia from early 80s onward. Conversely, favorable shifts in nonpolicy innovation variance imply movements in term premia that are at least qualitatively consistent with historical patterns.
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Garg, Uttam C., Zhi-Jie Zheng, Aaron R. Folsom, et al. "Short-term and long-term variability of plasma homocysteine measurement." Clinical Chemistry 43, no. 1 (1997): 141–45. http://dx.doi.org/10.1093/clinchem/43.1.141.
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Abstract Within-person and methodological variability of a given analyte are important elements in determining whether an individual has altered concentrations of that analyte. We report the short-term (1 month) within-person, between-person, and methodological variability of plasma homocysteine in 20 healthy participants from whom samples were drawn weekly for 4 weeks. The short-term between-person variance was high, whereas within-person and methodological variances were relatively very low, giving a high reliability coefficient (R) for homocysteine (R = 0.94). The long-term (30 months) reliability coefficient was 0.65, but was greatly influenced by an outlier (R = 0.82 with the outlier excluded). The data suggest that an individual’s plasma homocysteine concentration is relatively constant over at least 1 month, and a single measurement characterizes the average concentration reasonably well.
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Bachmaier, Martin, and Matthias Backes. "Variogram or Semivariogram? Variance or Semivariance? Allan Variance or Introducing a New Term?" Mathematical Geosciences 43, no. 6 (2011): 735–40. http://dx.doi.org/10.1007/s11004-011-9348-3.
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Hodges, James S., Yue Cui, Daniel J. Sargent, and Bradley P. Carlin. "Smoothing Balanced Single-Error-Term Analysis of Variance." Technometrics 49, no. 1 (2007): 12–25. http://dx.doi.org/10.1198/004017006000000408.
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Mammen, Enno, Jens Perch Nielsen, Michael Scholz, and Stefan Sperlich. "Conditional Variance Forecasts for Long-Term Stock Returns." Risks 7, no. 4 (2019): 113. http://dx.doi.org/10.3390/risks7040113.
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In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step procedure a fully nonparametric local-linear smoother and choose the set of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much less important at longer horizons regardless of the chosen model and that the homoscedastic historical average of the squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the one-year and five-year horizon.
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Clopath, Claudia, Tobias Bonhoeffer, Mark Hübener, and Tobias Rose. "Variance and invariance of neuronal long-term representations." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1715 (2017): 20160161. http://dx.doi.org/10.1098/rstb.2016.0161.
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The brain extracts behaviourally relevant sensory input to produce appropriate motor output. On the one hand, our constantly changing environment requires this transformation to be plastic. On the other hand, plasticity is thought to be balanced by mechanisms ensuring constancy of neuronal representations in order to achieve stable behavioural performance. Yet, prominent changes in synaptic strength and connectivity also occur during normal sensory experience, indicating a certain degree of constitutive plasticity. This raises the question of how stable neuronal representations are on the population level and also on the single neuron level. Here, we review recent data from longitudinal electrophysiological and optical recordings of single-cell activity that assess the long-term stability of neuronal stimulus selectivities under conditions of constant sensory experience, during learning, and after reversible modification of sensory input. The emerging picture is that neuronal representations are stabilized by behavioural relevance and that the degree of long-term tuning stability and perturbation resistance directly relates to the functional role of the respective neurons, cell types and circuits. Using a ‘toy’ model, we show that stable baseline representations and precise recovery from perturbations in visual cortex could arise from a ‘backbone’ of strong recurrent connectivity between similarly tuned cells together with a small number of ‘anchor’ neurons exempt from plastic changes. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.
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Carpenter, Stephen R., William A. Brock, Carl Folke, Egbert H. van Nes, and Marten Scheffer. "Allowing variance may enlarge the safe operating space for exploited ecosystems." Proceedings of the National Academy of Sciences 112, no. 46 (2015): 14384–89. http://dx.doi.org/10.1073/pnas.1511804112.
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Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2–4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.
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Eom, Young Ho, and Woon Wook Jang. "The Variance Swaps based on KOSPI200 Index and the Term Structure of Variance Risk Premium." Journal of Derivatives and Quantitative Studies 21, no. 4 (2013): 435–63. http://dx.doi.org/10.1108/jdqs-04-2013-b0004.
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This study examines whether the variance risk is a priced risk factor in Korea using the over-the-counter variance swap quotes and realized variance data. We also study the term structure of variance risk premium. The empirical results show that the model with 2 stochastic variance risk factors with jumps in return is required to fit the variance swap and realized variance data. The analyses with the estimated models suggest that the variance risk premium in Korea are highly negative and the size of the premium increase with the maturities, meaning that risk averse investors in Korea are willing to pay a premium to hedge variance risk.
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Jacobs, Robert A. "Bias/Variance Analyses of Mixtures-of-Experts Architectures." Neural Computation 9, no. 2 (1997): 369–83. http://dx.doi.org/10.1162/neco.1997.9.2.369.
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This article investigates the bias and variance of mixtures-of-experts (ME) architectures. The variance of an ME architecture can be expressed as the sum of two terms: the first term is related to the variances of the expert networks that comprise the architecture and the second term is related to the expert networks' covariances. One goal of this article is to study and quantify a number of properties of ME architectures via the metrics of bias and variance. A second goal is to clarify the relationships between this class of systems and other systems that have recently been proposed. It is shown that in contrast to systems that produce unbiased experts whose estimation errors are uncorrelated, ME architectures produce biased experts whose estimates are negatively correlated.
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Johnson, Travis L. "Risk Premia and the VIX Term Structure." Journal of Financial and Quantitative Analysis 52, no. 6 (2017): 2461–90. http://dx.doi.org/10.1017/s0022109017000825.
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The shape of the Chicago Board Options Exchange Volatility Index (VIX) term structure conveys information about the price of variance risk rather than expected changes in the VIX, a rejection of the expectations hypothesis. The second principal component, SLOPE, summarizes nearly all this information, predicting the excess returns of synthetic Standard & Poor’s (S&P) 500 variance swaps, VIX futures, and S&P 500 straddles for all maturities and to the exclusion of the rest of the term structure. SLOPE’s predictability is incremental to other proxies for the conditional variance risk premia, economically significant, and inconsistent with standard asset pricing models.
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Jaradat, Abdullah A. "Covariance Structures in Conventional and Organic Cropping Systems." International Journal of Agronomy 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/494026.
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Guidelines are needed to develop proper statistical analyses procedures and select appropriate models of covariance structures in response to expected temporal variation in long-term experiments. Cumulative yield, its temporal variance, and coefficient of variation were used in estimating and describing covariance structures in conventional and organic cropping systems of a long-term field experiment in a randomized complete block design. An 8-year database on 16 treatments (conventional and organic cropping systems, crop rotations, and tillage) was subjected to geostatistical, covariance structure, variance components, and repeated measures multivariate analyses using six covariance models under restricted maximum likelihood. Differential buildup of the cumulative effects due to crop rotations being repeated over time was demonstrated by decreasing structured and unstructured variances and increasing range estimates in the geostatistical analyses. The magnitude and direction of relationships between cumulative yield and its temporal variance, and coefficient of variation shaped the covariance structures of both cropping systems, crop rotations, and phases within crop rotations and resulted in significant deviations of organic management practices from their conventional counterparts. The unstructured covariance model was the best to fit most factor-variable combinations; it was the most flexible, but most costly in terms of computation time and number of estimated parameters.
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Çeviş, Ismaіl, and Cem Kadilar. "The Analysis of the Short-term Capital Movements by Using the VAR Model: The Case of Turkey." Pakistan Development Review 40, no. 3 (2001): 187–201. http://dx.doi.org/10.30541/v40i3pp.187-201.
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This paper investigates the relations among short-term capital inflows, government deficit, interest rate differentials, real exchange rate and some accounts of the balance of payments in Turkey in 1990s by using the vector autoregression (VAR) technique. The dynamic behaviours of each variable due to random shocks given to short-term foreign liabilities are captured by impulse response functions, and the portion of variance in the prediction for each variable in the system that is attributable to its own innovations and to shocks to other variables in the system is analysed by variance decomposition method. It is found that the policy of high interest-low exchange rate (hot money) is the main reason for the short-term capital inflows in Turkey, and we propose some main controls on capital inflows to limit some of the macroeconomic repercussions of these inflows.
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Park, Hyungbin. "Modified Mean-Variance Risk Measures for Long-Term Portfolios." Mathematics 9, no. 2 (2021): 111. http://dx.doi.org/10.3390/math9020111.
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This paper proposes modified mean-variance risk measures for long-term investment portfolios. Two types of portfolios are considered: constant proportion portfolios and increasing amount portfolios. They are widely used in finance for investing assets and developing derivative securities. We compare the long-term behavior of a conventional mean-variance risk measure and a modified one of the two types of portfolios, and we discuss the benefits of the modified measure. Subsequently, an optimal long-term investment strategy is derived. We show that the modified risk measure reflects the investor’s risk aversion on the optimal long-term investment strategy; however, the conventional one does not. Several factor models are discussed as concrete examples: the Black–Scholes model, Kim–Omberg model, Heston model, and 3/2 stochastic volatility model.
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Aït-Sahalia, Yacine, Mustafa Karaman, and Loriano Mancini. "The term structure of equity and variance risk premia." Journal of Econometrics 219, no. 2 (2020): 204–30. http://dx.doi.org/10.1016/j.jeconom.2020.03.002.
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Haaland, Thomas R., Jonathan Wright, and Irja I. Ratikainen. "Bet-hedging across generations can affect the evolution of variance-sensitive strategies within generations." Proceedings of the Royal Society B: Biological Sciences 286, no. 1916 (2019): 20192070. http://dx.doi.org/10.1098/rspb.2019.2070.
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In order to understand how organisms cope with ongoing changes in environmental variability, it is necessary to consider multiple adaptations to environmental uncertainty on different time scales. Conservative bet-hedging (CBH) represents a long-term genotype-level strategy maximizing lineage geometric mean fitness in stochastic environments by decreasing individual fitness variance, despite also lowering arithmetic mean fitness. Meanwhile, variance-prone (aka risk-prone) strategies produce greater variance in short-term payoffs, because this increases expected arithmetic mean fitness if the relationship between payoffs and fitness is accelerating. Using evolutionary simulation models, we investigate whether selection for such variance-prone strategies is counteracted by selection for bet-hedging that works to adaptively reduce fitness variance. In our model, variance proneness evolves in fine-grained environments (lower correlations among individuals in energetic state and/or payoffs), and with larger numbers of independent decision events over which resources accumulate prior to selection. Conversely, multiplicative fitness accumulation, caused by coarser environmental grain and fewer decision events selection, favours CBH via greater variance aversion. We discuss examples of variance-sensitive strategies in optimal foraging, migration, life histories and cooperative breeding using this bet-hedging perspective. By linking disparate fields of research studying adaptations to variable environments, we should be better able to understand effects of human-induced rapid environmental change.
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Kim, Michael Jong. "Variance Regularization in Sequential Bayesian Optimization." Mathematics of Operations Research 45, no. 3 (2020): 966–92. http://dx.doi.org/10.1287/moor.2019.1019.
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Sequential Bayesian optimization constitutes an important and broad class of problems where model parameters are not known a priori but need to be learned over time using Bayesian updating. It is known that the solution to these problems can in principle be obtained by solving the Bayesian dynamic programming (BDP) equation. Although the BDP equation can be solved in certain special cases (for example, when posteriors have low-dimensional representations), solving this equation in general is computationally intractable and remains an open problem. A second unresolved issue with the BDP equation lies in its (rather generic) interpretation. Beyond the standard narrative of balancing immediate versus future costs—an interpretation common to all dynamic programs with or without learning—the BDP equation does not provide much insight into the underlying mechanism by which sequential Bayesian optimization trades off between learning (exploration) and optimization (exploitation), the distinguishing feature of this problem class. The goal of this paper is to develop good approximations (with error bounds) to the BDP equation that help address the issues of computation and interpretation. To this end, we show how the BDP equation can be represented as a tractable single-stage optimization problem that trades off between a myopic term and a “variance regularization” term that measures the total solution variability over the remaining planning horizon. Intuitively, the myopic term can be regarded as a pure exploitation objective that ignores the impact of future learning, whereas the variance regularization term captures a pure exploration objective that only puts value on solutions that resolve statistical uncertainty. We develop quantitative error bounds for this representation and prove that the error tends to zero like o(n-1) almost surely in the number of stages n, which as a corollary, establishes strong consistency of the approximate solution.
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Danes, Sharon M., Kathryn Stafford, George Haynes, and Sayali S. Amarapurkar. "Family Capital of Family Firms." Family Business Review 22, no. 3 (2009): 199–215. http://dx.doi.org/10.1177/0894486509333424.
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The purpose was to present a family capital typology based on Sustainable Family Business Theory II and to document its relative contribution to short-term firm achievements and long-term sustainability using National Family Business Survey panel data. Family capital was defined as total owning-family resources composed of human, social, and financial capital. Family capital significantly contributed to firm achievements and sustainability. In the short term, all family capital types explained 13.5% of gross revenue variance and 4% of owner’s success perception variance. In the long term, all family capital types explained 26.7% of gross revenue variance and 11.6% of owner’s success perception variance.
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Gallagher, S. K., L. K. Johnson, and D. B. Milne. "Short-term and long-term variability of indices related to nutritional status. I: Ca, Cu, Fe, Mg, and Zn." Clinical Chemistry 35, no. 3 (1989): 369–73. http://dx.doi.org/10.1093/clinchem/35.3.369.
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Abstract Five free-living women (ages 28-38 y) and five women (ages 23-44 y) residing in a metabolic unit and eating a constant diet were assessed for variation in indices related to mineral nutrition. Blood was sampled once a month for five months, once a week for five weeks, and once a day for five days to assess analytical and biological variability. Analytical variability was determined by using concurrently run duplicate control samples prepared from plasma or serum pools. Of the measured indices, serum ferritin varied most, with intra-individual variance of 4.72% to 18.0%. Much of this variance may have been because of changes in iron status or in the analytical technique used. Intra-individual month-to-month variance for other indices ranged from 17% for superoxide dismutase (EC 1.15.1.1) to 1.5% for calcium. Correction for long-term analytical variation indicated that most of the variance was associated with the biological component. The higher biological variabilities of some indices, including ferritin or superoxide dismutase, need to be considered when nutritional status is being evaluated or when serial observations are made over a protracted period in clinical studies or trials.
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Wilber, Anne C., G. Louis Smith, Shashi K. Gupta, and Paul W. Stackhouse. "Annual Cycles of Surface Shortwave Radiative Fluxes." Journal of Climate 19, no. 4 (2006): 535–47. http://dx.doi.org/10.1175/jcli3625.1.
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Abstract The annual cycles of surface shortwave flux are investigated using the 8-yr dataset of the surface radiation budget (SRB) components for the period July 1983–June 1991. These components include the downward, upward, and net shortwave radiant fluxes at the earth's surface. The seasonal cycles are quantified in terms of principal components that describe the temporal variations and empirical orthogonal functions (EOFs) that describe the spatial patterns. The major part of the variation is simply due to the variation of the insolation at the top of the atmosphere, especially for the first term, which describes 92.4% of the variance for the downward shortwave flux. However, for the second term, which describes 4.1% of the variance, the effect of clouds is quite important and the effect of clouds dominates the third term, which describes 2.4% of the variance. To a large degree the second and third terms are due to the response of clouds to the annual cycle of solar forcing. For net shortwave flux at the surface, similar variances are described by each term. The regional values of the EOFs are related to climate classes, thereby defining the range of annual cycles of shortwave radiation for each climate class.
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Steele, Bernard W., Edward Wang, Glenn Palomaki, George G. Klee, Ronald J. Elin, and David L. Witte. "Sources of Variability." Archives of Pathology & Laboratory Medicine 125, no. 2 (2001): 183–90. http://dx.doi.org/10.5858/2001-125-0183-sov.
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Abstract Objective.—To determine the magnitudes and sources of analytic variation in testing for therapeutic drugs. Specifically, among laboratories using the same analytic method, to compare the within-laboratory variation (including both short- and long-term variation) with the between-laboratory variation. Design.—Four identical challenges were prepared from a lyophilized pool of spiked sera and were sent in pairs 4 months apart to laboratories participating in a nationwide proficiency-testing program. For each of 25 drugs, the variability in reported results from laboratories using the same method was investigated using nested analysis of variance. Setting.—The first 2 mailings of the College of American Pathologists Therapeutic Drug Monitoring Survey, 1996, sets Z and ZM. Main Outcome Measures.—For each drug, total variance was partitioned into within- and between-laboratory components for common methods. The within-laboratory component was further partitioned into short- and long-term components. Participants.—The approximately 5000 laboratories enrolled in the survey. Results.—For the 25 drugs, the average percentages of the total variance due to short-term, within-laboratory variance; long-term, within-laboratory variance; between-laboratory variance; and total laboratory variance were 25.0% (range, 8.8–50.6%), 57.8% (35.3–73.7%), 17.3% (5.0–35.4%), and 82.7% (64.6–95.0%), respectively. Conclusion.—For all drugs tested, the within-laboratory component of variance was greater than the between-laboratory component of variance. Within laboratories, the magnitude of the long-term component was generally greater than the magnitude of the short-term component. This information will be helpful in determining the clinical utility of various drug assays and in evaluating the appropriateness of regulations involving therapeutic drug testing.
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Azizmohammad Looha, Mehdi, Mohamad Amin Pourhoseingholi, Seyyed Vahid Hosseini, and Soheila Khodakarim. "Mismeasured Covariate in the Long-Term Survival of Colorectal Cancer." Galen Medical Journal 8 (July 8, 2019): 1413. http://dx.doi.org/10.31661/gmj.v8i0.1413.
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Background: Colorectal cancer (CRC) is one of the most important causes of morbidity and mortality worldwide. This study aimed to determine the effect of measurement error of risk factors on the cure fraction of CRC patients. Materials and Methods: This study was conducted using the medical records of 346 patients with CRC, who were followed up between 2006 and 2017 in Shiraz, Iran. In our data, lymph node ratio (LNR) was a characteristic measuring with error. This variable was used in the model with 0.04 and 0.8 of error variance. Nonmixture nonparametric cure rate model and its corrected forms, simulation-extrapolation (SIMEX) and corrected score (CS), were applied to the data. Results: In noncured cases, the mean survival time was 1115.45 (95% confidence interval, 1043.60-1187.30) days. The 1-, 3-, and 5-year survival rates were 0.93, 0.71, and 0.65, respectively. The proportion of cured patients was 65.2%. The SIMEX method did not change the effect of LNR substantially on cure fraction as compared with the naive method when the variance of measurement error was 0.04 and 0.80. The CS method changed the effect of LNR on cure fraction even when the variance of measurement error was 0.04. Conclusion: The best method to assess the effect of LNR on cure fraction was the naive method, and the CS method was not deemed to be a valid method to correct the measurement error in LNR. [GMJ.2019;8:e1413]
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Romano, Francesco, and Christian Kuehn. "Analysis and Predictability of Tipping Points with Leading-Order Nonlinear Term." International Journal of Bifurcation and Chaos 28, no. 08 (2018): 1850103. http://dx.doi.org/10.1142/s0218127418501031.
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Tipping points have been actively studied in various applications as well as from a mathematical viewpoint. A main technique to theoretically understand early-warning signs for tipping points is to use the framework of fast–slow stochastic differential equations. A key assumption in many arguments for the existence of variance and auto-correlation growth before a tipping point is to use a linearization argument, i.e. the leading-order term governing the deterministic (or drift) part of a stochastic differential equation is linear. This assumption guarantees a local approximation via an Ornstein–Uhlenbeck process in the normally hyperbolic regime before, but sufficiently bounded away from, a bifurcation. In this paper, we generalize the situation to leading-order nonlinear terms for the setting of one fast variable. We work in the quasi-steady regime and prove that the fast variable has a well-defined stationary distribution and we calculate the scaling law for the variance as a bifurcation-induced tipping point is approached. We cross-validate the scaling law numerically. Furthermore, we provide a computational study for the predictability using early-warning signs for leading-order nonlinear terms based upon receiver-operator characteristic curves.
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Queraltó, J. M., J. C. Boyd, and E. K. Harris. "On the calculation of reference change values, with examples from a long-term study." Clinical Chemistry 39, no. 7 (1993): 1398–403. http://dx.doi.org/10.1093/clinchem/39.7.1398.
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Abstract Reference change values (sometimes called critical differences) indicate statistically important changes between test values obtained on two occasions. They are commonly computed from the median (or mean) within-subject variance observed in repeated test measurements on a number of subjects. With this computational approach, all observed within-subject variances are assumed to be estimates of a constant true variance, the same for all individuals. Moreover, any possible correlation between successive values is almost always ignored. This simplified methodology differs from the method originally proposed for computing reference change values, which accounts for variability in true variances and for serial correlation. From data obtained from repeated measurements over 2 to 5 years in 72 physically healthy subjects, we computed and compared reference change values in 18 serum analytes, using the simplified method and the originally proposed procedure. Although the original method is more complicated and requires a computer program, we believe that it produces more-reliable reference change values than those obtained by the simplified approach. The former are generally larger, but remain sensitive to clinically important changes in the individual.
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Li, Ran, and Xian Jiu Guo. "Improved Term Selection Algorithm Based on Variance in Text Categorization." Advanced Materials Research 765-767 (September 2013): 735–38. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.735.
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This article improves the algorithm of term weighting in automated text classification. The traditional TFIDF algorithm is a common method that is used to measure term weighting in text classification.However, the algorithm does not take the distribution of terms in inter-class. In order to solve the problem, variance which describes the distribution of terms in inter-class and intra-class is used to revise TFIDF algorithm. This article mainly researched about the construction of LFHW term sets and new approaches to term weighting, These new approaches are also applied to the hierarchical classification system.Compared with traditional TFIDF algorithm ,the results of simulation experiment have demonstrated that the improved TFIDF algorithm can get better classification results.
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Ahlonsou, Ceptime Galilée, Epiphane Sodjinou, Bagagnidé François Koladjo, and Romain Glèlè Kakaï. "Assessing performance of directional output distance function: Simulation-based Analysis." African Journal of Applied Statistics 10, no. 02 (2023): 1451–68. http://dx.doi.org/10.16929/ajas/2023.1451.277.
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This study examined the effect of sample sizes, distribution of the noise term and variance inefficiency term performance on directional output distance function (<i>DODF</i>) through Monte Carlo experiments. Sample sizes from 100 to 500 at the interval length of 100, variance of the inefficiency term (\(\sigma_u^{2}=0.05, \ 0.8)) and distribution of the noise term with normal and Student-t distribution levels were considered. Results revealed that larger the sample size and the variance of inefficiency term are, better directional output distance function performed. However, when the sample size exceeds 300, no impact is observed on the performance of <i>DODF</i>
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Filip, Ioan, Florin Dragan, Iosif Szeidert, and Adriana Albu. "Minimum-Variance Control System with Variable Control Penalty Factor." Applied Sciences 10, no. 7 (2020): 2274. http://dx.doi.org/10.3390/app10072274.
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The present paper proposes (as the main contribution) an additional self-tuning mechanism for an adaptive minimum-variance control system, whose main goal is to extend its functionality for a large value range of unmeasurable perturbations which disturb the controlled process. Through the standard design procedure, a minimum variance controller uses by default an internal self-tuning mechanism based on the process parameter estimates. However, the main parameter which overwhelmingly influences the control performance is the control penalty factor ( ρ ) . This parameter weights the term that describes the control variance in a criterion function whose minimization is the starting point of the control law design. The classical minimum-variance control involves an off-line tuning of this parameter, its value being set as constant throughout the entire operating regime. Based on the measurement of the process output error, the contribution of the proposed strategy consists in a real-time tuning of the control penalty factor, to ensure the stability of the control system, even under conditions of high disturbances. The proposed tuning mechanism adjusts this parameter by implementing a bipositional switching strategy based on a sharp hysteresis loop. Therefore, instead of the standard solution that involves a constant value of the control penalty factor ρ (a priori computed and set), this paper proposes a dual value for this controller parameter. The main objective is to allow the controlled process to operate in a stable fashion even in more strongly disturbed regimes (regimes where the control system becomes unstable and is usually switched off for safety reasons). To validate the proposed strategy, an induction generator integrated into a wind energy conversion system was considered as controlled plant. Operating under the action of strong disturbances (wind gusts, electrical load variations), the extension of safe operating range (thus avoiding the system disengagement) is an important goal of such a control system.
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Yanou, Akira. "Extension Method of Generalized Minimum Variance Control Using Noise Term." IEEJ Transactions on Electronics, Information and Systems 141, no. 3 (2021): 398–99. http://dx.doi.org/10.1541/ieejeiss.141.398.
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Greenhall, C. A., D. A. Howe, and D. B. Percival. "Total variance, an estimator of long-term frequency stability [standards]." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 46, no. 5 (1999): 1183–91. http://dx.doi.org/10.1109/58.796124.
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Dotsis, George. "The market price of risk of the variance term structure." Journal of Banking & Finance 84 (November 2017): 41–52. http://dx.doi.org/10.1016/j.jbankfin.2015.10.008.
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BOGERT, JAMES DAWSON. "EXPLAINING VARIANCE IN THE PERFORMANCE OF LONG-TERM CORPORATE BLOCKHOLDERS." Strategic Management Journal 17, no. 3 (1996): 243–49. http://dx.doi.org/10.1002/(sici)1097-0266(199603)17:3<243::aid-smj802>3.0.co;2-d.
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Basse, Alexander, Doron Callies, Anselm Grötzner, and Lukas Pauscher. "Seasonal effects in the long-term correction of short-term wind measurements using reanalysis data." Wind Energy Science 6, no. 6 (2021): 1473–90. http://dx.doi.org/10.5194/wes-6-1473-2021.
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Abstract. Measure–correlate–predict (MCP) approaches are often used to correct wind measurements to the long-term wind conditions on-site. This paper investigates systematic errors in MCP-based long-term corrections which occur if the measurement on-site covers only a few months (seasonal biases). In this context, two common linear MCP methods are tested and compared with regard to accuracy in mean, variance, and turbine energy production – namely, variance ratio (VR) and linear regression with residuals (LR). Wind measurement data from 18 sites with different terrain complexity in Germany are used (measurement heights between 100 and 140 m). Six different reanalysis data sets serve as the reference (long-term) wind data in the MCP calculations. All these reanalysis data sets showed an overpronounced annual course of wind speed (i.e., wind speeds too high in winter and too low in summer). However, despite the mathematical similarity of the two MCP methods, these errors in the data resulted in very different seasonal biases when either the VR or LR methods were used for the MCP calculations. In general, the VR method produced overestimations of the mean wind speed when measuring in summer and underestimations in the case of winter measurements. The LR method, in contrast, predominantly led to opposite results. An analysis of the bias in variance did not show such a clear seasonal variation. Overall, the variance error plays only a minor role for the accuracy in energy compared to the error in mean wind speed. Besides the experimental analysis, a theoretical framework is presented which explains these phenomena. This framework enables us to trace the seasonal biases to the mechanics of the methods and the properties of the reanalysis data sets. In summary, three aspects are identified as the main influential factors for the seasonal biases in mean wind speed: (1) the (dis-)similarity of the real wind conditions on-site in correlation and correction period (representativeness of the measurement period), (2) the capability of the reference data to reproduce the seasonal course of wind speed, and (3) the regression parameter β1 (slope) of the linear MCP method. This theoretical framework can also be considered valid for different measurement durations, other reference data sets, and other regions of the world.
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О., І. Васецька. "АБРЕВІАТУРНІ ТА СИМВОЛЬНІ ДУБЛЕТИ В СИНТАКСИЧНІЙ ТЕРМІНОЛОГІЇ УКРАЇНСЬКОЇ МОВИ". Збірник наукових праць ХНПУ імені Г.С. Сковороди "Лінгвістичні дослідження", № 44 (7 листопада 2016): 168–74. https://doi.org/10.5281/zenodo.165102.
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One of the most important tasks is studying of special features of term–abbreviations and term–symbols in scientific texts. These units in contexts are mainly used with the only indication to interpretation that formalize information presenting and affirms their functioning as independent units together with detailed variants (analogues). In the article the status of abbreviation and symbolic duplets is defined as substitutes, also types of abbreviation duplets are distinguished; symbolic duplets are examined as demonstration of the author’s making of terms. The subject is syntactic terminology of the Ukrainian language, and the object is abbreviation and symbolic variants of the term system of syntax. The aim of the article is to analyze peculiarities of abbreviation and symbols functioning in terminology of the Ukrainian language syntax. The tasks of this work are to define the origin of term – abbreviations and symbols and to classify abbreviation duplets in syntactical system of terms. Analysis of Ukrainian syntactic terms allowed distinguishing the following types of abbreviations: initial abbreviations (lettered, sound abbreviations and combined). We are going to distinguish symbol words as the manifestation of author’s term forming. The process of term substitution in texts is caused by logical, terminological, linguistic reasons, and it also partially depends on text style where it is used.
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Ningsih, Nuri Rahayu, Budi Rusdianto, Kardina Siregar, Andria Zulfa, and Dwita Sakuntala. "Implications of Macro Economic Conditions for Banking Effectiveness in Indonesia." PKM-P 8, no. 2 (2024): 386–95. https://doi.org/10.32832/jurma.v8i2.2415.
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This research aims to determine banking effectiveness. The variables in this research are Capital Adequacy Ratio (CAR), Non-Performing Loans (NPL), Economic Growth (GDP), Inflation, and Exchange Rates. The analytical method used in this research is the Vector Auto Regression (VAR) model with the Impulse Response Function (IRF) test, Forecast Error Variance Decomposition (FEVD), stationarity test, cointegration test, structural lag stability test, and optimal lag length test. The results of Vector Autoregressive research using a lag 2 basis show that there is a contribution from each variable to the variable itself and other variables. The results of the Vector Autoregression analysis also show that the past variable (t-1) contributes to the current variable, both the variable itself and other variables. From the analysis results, there is a reciprocal relationship between one variable and another variable. Response Function analysis shows that there is a response of other variables to changes in one variable in the short, medium, and long term, and it is known that the stability of the response of all variables is formed in 5 years or long term. Variance Analysis Decomposition shows the existence of variables that have the largest contribution to the variable itself in the short, medium, and long term, such as INF and KURS. Meanwhile, other variables that have the greatest influence on the variable itself and are supported by other variables in the short, medium, and long term are CAR and NPL which are most influenced by the EXCHANGE and GDP.
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VanderSchaaf, Curtis L., and David South. "Biological, Economic, and Management Implications of Weighted Least Squares." Southern Journal of Applied Forestry 33, no. 2 (2009): 53–57. http://dx.doi.org/10.1093/sjaf/33.2.53.
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Abstract An assumption of ordinary least squares (OLS) is constant variance across the domain of a regressor. Often, however, the random error term variance is not constant when modeling biological data and therefore weighted least squares (WLS) is commonly used to estimate parameters. Less emphasis is placed on observations of the dependent variable with larger variances when using WLS, which is thought to produce more “efficient” parameter estimates. Statisticians often use WLS instead of OLS when the random error variance is not constant. However, as natural resource managers, we are often most interested in values of the dependent variable where the variance is greatest. What then are the biological, economic, and management implications of using WLS versus OLS in natural resource modeling? In this article, parameters of the combined-variable volume equation were estimated for individual trees in loblolly pine plantations using both OLS and WLS. A growth-and-yield model was used to predict stand development over time of two planting densities (303 and 1,090 seedlings/ac) and individual tree volumes were predicted using OLS and WLS parameter estimates. Economic analyses were then conducted. Our results show that the choice of OLS or WLS can have a substantial impact on predicted economic returns. Thus, when using WLS, landowners may decide to invest in additional management treatments that may, in fact, not be economically feasible. This study provides further evidence that landowners need to be aware of model structures when basing harvest-age decisions on growth and yield projections.
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Hsieh, Ming-hua, Jennifer L. Wang, Yu-Fen Chiu, and Yen-Chih Chen. "Valuation of variable long-term care Annuities with Guaranteed Lifetime Withdrawal Benefits: A variance reduction approach." Insurance: Mathematics and Economics 78 (January 2018): 246–54. http://dx.doi.org/10.1016/j.insmatheco.2017.09.017.
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García-Fiñana, Marta, and Luis M. Cruz-Orive. "FRACTIONAL TREND OF THE VARIANCE IN CAVALIERI SAMPLING." Image Analysis & Stereology 19, no. 2 (2011): 71. http://dx.doi.org/10.5566/ias.v19.p71-79.
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Cavalieri sampling is often used to estimate the volume of an object with systematic sections a constant distance T apart. The variance of the corresponding estimator can be expressed as the sum of the extension term (which gives the overall trend of the variance and is used to estimate it), the 'Zitterbewegung' (which oscillates about zero) and higher order terms. The extension term is of order T2m+2 for small T, where m is the order of the first non-continuous derivative of the measurement function f, (namely of the area function if the target is the volume). A key condition is that the jumps of the mth derivative f (m) of f are finite. When this is not the case, then the variance exhibits a fractional trend, and the current theory fails. Indeed, in practice the mentioned trend is often of order T2q+2, typically with 0 <q <1. We obtain a general representation of the variance, and thereby of the extension term, by means of a new Euler-MacLaurin formula involving fractional derivatives of f. We also present a new and general estimator of the variance, see Eq. 26a, b, and apply it to real data (white matter of a human brain).
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Wei, Ming, Armando Caballero, and William G. Hill. "Selection Response in Finite Populations." Genetics 144, no. 4 (1996): 1961–74. http://dx.doi.org/10.1093/genetics/144.4.1961.
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Formulae were derived to predict genetic response under various selection schemes assuming an infinitesimal model. Account was taken of genetic drift, gametic (linkage) disequilibrium (Bulmer effect), inbreeding depression, common environmental variance, and both initial segregating variance within families (σAW02) and mutational (σM2) variance. The cumulative response to selection until generation t(CRt) can be approximated asCRt≈R0[t−β(1−σAW∞2σAW02)t24Ne]−Dt2Ne,where Ne is the effective population size, σAW∞2=NeσM2 is the genetic variance within families at the steady state (or one-half the genic variance, which is unaffected by selection), and D is the inbreeding depression per unit of inbreeding. R 0 is the selection response at generation 0 assuming preselection so that the linkage disequilibrium effect has stabilized. β is the derivative of the logarithm of the asymptotic response with respect to the logarithm of the within-family genetic variance, i.e., their relative rate of change. R 0 is the major determinant of the short term selection response, but σM2, Ne and β are also important for the long term. A selection method of high accuracy using family information gives a small Ne and will lead to a larger response in the short term and a smaller response in the long term, utilizing mutation less efficiently.
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Wang, Wenpeng, Yuelong Zhu, Bo Liu, Yuanfang Chen, and Xu Zhao. "Innovative Variance Corrected Sen’s Trend Test on Persistent Hydrometeorological Data." Water 11, no. 10 (2019): 2119. http://dx.doi.org/10.3390/w11102119.
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Trend detection in observations helps one to identify anthropogenic forces on natural hydrological and climatic systems. Hydrometeorological data are often persistent over time that deviates from the assumption of independence used by many statistical methods. A recently proposed Sen’s trend test claimed to be free of this problem and thereby received widespread attention. However, both theoretical derivation and stochastic simulation of the current study implies that persistence inflates the trend significance, leading to false trends. To tackle this problem, we incorporate the feature of persistence into the variance of the trend test statistic, whereby an innovative variance-corrected Sen’s trend test is developed. Two theoretical variances of the trend test statistic are newly derived to account for short-term and long-term persistent behavior. The original variance for independent data is also corrected because of its negative bias. A stepwise procedure, including steps to specify the underlying persistent behavior and to test trend with new statistic, is outlined for performing the new test on factual data. Variance-corrected Sen’s trend test can effectively restore the inflated trend significance back to its nominal state. This study may call for the reassessment of published results of the original Sen’s trend test on data with persistence.
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Du, Manuel, Richard Bernstein, Andreas Hoppe, and Kaspar Bienefeld. "Short-term effects of controlled mating and selection on the genetic variance of honeybee populations." Heredity 126, no. 5 (2021): 733–47. http://dx.doi.org/10.1038/s41437-021-00411-2.
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AbstractDirectional selection in a population yields reduced genetic variance due to the Bulmer effect. While this effect has been thoroughly investigated in mammals, it is poorly studied in social insects with biological peculiarities such as haplo-diploidy or the collective expression of traits. In addition to the natural adaptation to climate change, parasites, and pesticides, honeybees increasingly experience artificial selection pressure through modern breeding programs. Besides selection, many honeybee breeding schemes introduce controlled mating. We investigated which individual effects selection and controlled mating have on genetic variance. We derived formulas to describe short-term changes of genetic variance in honeybee populations and conducted computer simulations to confirm them. Thereby, we found that the changes in genetic variance depend on whether the variance is measured between queens (inheritance criterion), worker groups (selection criterion), or both (performance criterion). All three criteria showed reduced genetic variance under selection. In the selection and performance criteria, our formulas and simulations showed an increased genetic variance through controlled mating. This newly described effect counterbalanced and occasionally outweighed the Bulmer effect. It could not be observed in the inheritance criterion. A good understanding of the different notions of genetic variance in honeybees, therefore, appears crucial to interpreting population parameters correctly.
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Steele, Bernard W., Edward Wang, Darryl E. Palmer-Toy, Anthony A. Killeen, Ronald J. Elin, and George G. Klee. "Total Long-term Within-Laboratory Precision of Cortisol, Ferritin, Thyroxine, Free Thyroxine, and Thyroid-Stimulating Hormone Assays Based on a College of American Pathologists Fresh Frozen Serum Study: Do Available Methods Meet Medical Needs for Precision?" Archives of Pathology & Laboratory Medicine 129, no. 3 (2005): 318–22. http://dx.doi.org/10.5858/2005-129-318-tlwpoc.
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AbstractContext.—It is important that the total long-term precision of laboratory methods meet the medical needs of the patients being served.Objectives.—To determine the long-term within- and between-laboratory variation of cortisol, ferritin, thyroxine, free thyroxine, and thyroid-stimulating hormone measurements using commonly available methods and to determine if these variations are within accepted medical needs.Design.—Two vials of pooled frozen serum were mailed 6 months apart to laboratories participating in 2 separate College of American Pathologists surveys. The data from those laboratories that analyzed an analyte in both surveys were used to determine for each method the total variance and the within- and between-laboratory components.Setting.—The study included the A mailing of the 2003 College of American Pathologists Ligand Survey and the C mailing of the Chemistry Survey.Main Outcome Measures.—For each analyte, total variance was partitioned into within- and between-laboratory components for each analytic method. The within-laboratory variations were then compared with imprecision criteria based on biological variation.Participants.—The laboratories that reported results on the same analyte using the same method in both surveys.Results.—For each analyte, the median of the long-term within-laboratory variances of each peer group was 78% to 95% of its total-survey variance, and the median long-term within-laboratory coefficients of variation varied from 5.1% to 7.6%. The number of methods that met within-laboratory imprecision goals based on biological criteria were 5 of 5 for cortisol; 5 of 7 for ferritin; 0 of 7 for thyroxine and free thyroxine; and 8 of 8 for thyroid-stimulating hormone.Conclusions.—For all analytes tested, the total within-laboratory component of variance was the major source of variability in this study. In addition, there are several methods, especially for thyroxine and free thyroxine, that may not meet analytic goals in terms of their imprecision.
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Turner, Thomas F., John P. Wares, and John R. Gold. "Genetic Effective Size Is Three Orders of Magnitude Smaller Than Adult Census Size in an Abundant, Estuarine-Dependent Marine Fish (Sciaenops ocellatus)." Genetics 162, no. 3 (2002): 1329–39. http://dx.doi.org/10.1093/genetics/162.3.1329.
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Abstract Using eight microsatellite loci and a variety of analytical methods, we estimated genetic effective size (Ne) of an abundant and long-lived marine fish species, the red drum (Sciaenops ocellatus), in the northern Gulf of Mexico (Gulf). The ratio Ne/N, where short-term variance Ne was estimated via the temporal method from shifts in allele-frequency data over four cohorts and where N reflected a current estimate of adult census size in the northern Gulf, was ∼0.001. In an idealized population, this ratio should approximate unity. The extraordinarily low value of Ne/N appears to arise from high variance in individual reproductive success and perhaps more importantly from variance in productivity of critical spawning and nursery habitats located in spatially discrete bays and estuaries throughout the northern Gulf. An estimate of Ne based on a coalescent approach, which measures long-term, inbreeding effective size, was four orders of magnitude lower than the estimate of current census size, suggesting that factors presently driving Ne/N to low values among red drum in the northern Gulf may have operated similarly in the past. Models that predict Ne/N exclusively from demographic and life-history features will seriously overestimate Ne if variance in reproductive success and variance in productivity among spatially discrete demes is underestimated. Our results indicate that these variances, especially variance in productivity among demes, must be large for red drum. Moreover, our study indicates that vertebrate populations with enormous adult census numbers may still be at risk relative to decline and extinction from genetic factors.
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Messineo, Cristina. "Variación conceptual y formal del término educación bilingüe intercultural (ebi) en distintos tipos de discursos." Terminology 8, no. 1 (2002): 113–39. http://dx.doi.org/10.1075/term.8.1.06mes.
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This paper studies the use of the term educación bilingüe intercultural (ebi) (‘intercultural bilingual education’) both in specialized discourse as well as in non-specialized documents from the perspective of a proposal for a terminology which is at variance with the traditional point of view, oriented towards terminology normalization and prescription. The focus here is on communication: according to this approach, terms are considered as units of natural language with a capacity for reference, but, like words, they can also have other functions (expressive, conative, etc.), and can be used in different communicative settings. This analysis allows us to explain the term intercultural bilingual education in discourses produced in different socio-cultural situations, to observe the degree of competence the producers of such discourses have of such a term and to describe the formal and conceptual variation of the term according to the users and the type of text.
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Kvale, Mark N., and Christoph E. Schreiner. "Short-Term Adaptation of Auditory Receptive Fields to Dynamic Stimuli." Journal of Neurophysiology 91, no. 2 (2004): 604–12. http://dx.doi.org/10.1152/jn.00484.2003.
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Short-term adaptation and recovery from adaptation have a strong impact on the processing of dynamic stimuli. Adaptive effects on neuronal activity have been studied most commonly for changes in first-order statistics of stimuli such as stepwise increments or decrements in stimulus amplitude. However, changes in higher moment statistics, such as the variance of the amplitude distribution in visual stimuli, also can invoke pronounced adaptation behavior. We demonstrate here that neurons in the inferior colliculus (ICC) of the cat show adaptation to dynamic auditory stimuli that differ in the variance of their modulation depth distribution. In addition, it is shown that neurons show adaptation to other higher moment statistics (e.g., kurtosis) of the modulation envelope. The time course of adaptation is specific for the altered stimulus property and the direction of parameter change. The use of dynamic stimuli allows an estimate of the effects of the adaptation on the temporal response properties of the neurons. We demonstrate that temporal receptive fields of neurons undergo change during the course of adaptation. We show that adaptation to variance in the ICC has many similarities to that in the retina and suggest that adaptation to variance is a general property of sensory systems that allows them to effectively deal with a nonstationary environment.
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Kyriakou, Ioannis, Parastoo Mousavi, Jens Perch Nielsen, and Michael Scholz. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons." Mathematics 9, no. 6 (2021): 620. http://dx.doi.org/10.3390/math9060620.
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The fundamental interest of investors in econometric modeling for excess stock returns usually focuses either on short- or long-term predictions to individually reduce the investment risk. In this paper, we present a new and simple model that contemporaneously accounts for short- and long-term predictions. By combining the different horizons, we exploit the lower long-term variance to further reduce the short-term variance, which is susceptible to speculative exuberance. As a consequence, the long-term pension-saver avoids an over-conservative portfolio with implied potential upside reductions given their optimal risk appetite. Different combinations of short and long horizons as well as definitions of excess returns, for example, concerning the traditional short-term interest rate but also the inflation, are easily accommodated in our model.
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Eladly, Salah Mohamed. "Sources Allocation on Risk Performance of Egyptian Insurance Companies." Journal of Management and Strategy 12, no. 3 (2021): 32. http://dx.doi.org/10.5430/jms.v12n3p32.
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The main objective of current paper was to investigate the relationship between sources allocations measured by (external sources to total assets- free investment and allocated investment to total assets) on risk performance measured by financial risk (standard deviation of return on equity) business risk (standard deviation of return on assets) using ARDL and GARCH model, using a sample of 19 Egyptian insurance companies over a 21 year period form 1999 – 2019, the findings indicate that There is a significant negative linear relationships between the independent variable in terms of capital structure and assets structure on dependent variable standard deviation of return on equity (Y1) at a Significant level less than (0.05). Also there is a significant positive linear relationship between the independent variable in terms of assets structure and dependent variable standard deviation of return on assets (Y2) at a significant level less than (0.001). with regard to ARCH and GARCH result shows the There is a significant positive effect of the ARCH term, measured as the lag of the squared residual from the mean equation, and the GARCH term, Last period’s forecast variance, at a significant level less than (0.05). It means that the high volatility in the conditional variance of standard deviation of return on assets y2. also The sum of the two parameters of: (α+β) in the GARCH model (1, 1) whether the random error are distributed according to normal distribution approaches the positive one, which indicates that the two conditions of non-negative variance, and the variance is not inflated are satisfied, and that Indication of the continuity of volatility shocks in the standard deviation of return on assets (Y2).