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Journal articles on the topic 'Minimum limiting variance of the estimate'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Turovsky, A. L., and O. V. Drobik. "PROCEDURE FOR EVALUATION OF THE SUPPORTING FREQUENCY SIGNAL OF THE SATELLITE COMMUNICATION SYSTEM IN CONTINUOUS MODE." Radio Electronics, Computer Science, Control, no. 2 (June 26, 2021): 28–38. http://dx.doi.org/10.15588/1607-3274-2021-2-3.

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Context. One of the features of satellite communication systems is the advantageous use in them during the reception of the signal in the continuous mode of phase modulation of signals intended for the transmission of useful information. The use of this type of modulation requires solving the problem of estimating the carrier frequency of the signal. And the estimation itself is reduced to the problem of estimating the frequency of the maximum in the spectrum of a fragment of a sinusoidal signal against the background of additive Gaussian noise. The article considers the process of estimating

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Pandey, Gaurav, James McBride, Silvio Savarese, and Ryan Eustice. "Automatic Targetless Extrinsic Calibration of a 3D Lidar and Camera by Maximizing Mutual Information." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 2053–59. http://dx.doi.org/10.1609/aaai.v26i1.8379.

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This paper reports on a mutual information (MI) based algorithm for automatic extrinsic calibration of a 3D laser scanner and optical camera system. By using MI as the registration criterion, our method is able to work in situ without the need for any specific calibration targets, which makes it practical for in-field calibration. The calibration parameters are estimated by maximizing the mutual information obtained between the sensor-measured surface intensities. We calculate the Cramer-Rao-Lower-Bound (CRLB) and show that the sample variance of the estimated parameters empirically approaches

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Robin, Jean-Marc, and Richard J. Smith. "TESTS OF RANK." Econometric Theory 16, no. 2 (2000): 151–75. http://dx.doi.org/10.1017/s0266466600162012.

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This paper considers tests for the rank of a matrix for which a root-T consistent estimator is available. However, in contrast to tests associated with the minimum chi-square and asymptotic least squares principles, the estimator's asymptotic variance matrix is not required to be either full or of known rank. Test statistics based on certain estimated characteristic roots are proposed whose limiting distributions are a weighted sum of independent chi-squared variables. These weights may be simply estimated, yielding convenient estimators for the limiting distributions of the proposed statistic

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4

Hambly, Ben. "On the limiting distribution of a supercritical branching process in a random environment." Journal of Applied Probability 29, no. 3 (1992): 499–518. http://dx.doi.org/10.2307/3214889.

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We consider an increasing supercritical branching process in a random environment and obtain bounds on the Laplace transform and distribution function of the limiting random variable. There are two possibilities that can be distinguished depending on the nature of the component distributions of the environment. If the minimum family size of each is 1, the growth will be as a power depending on a parameter α. If the minimum family sizes of some are greater than 1, it will be exponential, depending on a parameter γ. We obtain bounds on the distribution function analogous to those found for the s

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Hambly, Ben. "On the limiting distribution of a supercritical branching process in a random environment." Journal of Applied Probability 29, no. 03 (1992): 499–518. http://dx.doi.org/10.1017/s0021900200043345.

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We consider an increasing supercritical branching process in a random environment and obtain bounds on the Laplace transform and distribution function of the limiting random variable. There are two possibilities that can be distinguished depending on the nature of the component distributions of the environment. If the minimum family size of each is 1, the growth will be as a power depending on a parameter α. If the minimum family sizes of some are greater than 1, it will be exponential, depending on a parameter γ. We obtain bounds on the distribution function analogous to those found for the s

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Ghasemi Naraghi, Mehdi, and Yousef Alipouri. "Minimum variance lower bound estimation with Gaussian Process models." Transactions of the Institute of Measurement and Control 40, no. 6 (2017): 1799–807. http://dx.doi.org/10.1177/0142331217690802.

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In this paper, we utilize the probability density function of the data to estimate the minimum variance lower bound (MVLB) of a nonlinear system. For this purpose, the Gaussian Process (GP) model has been used. With this model, given a new input and based on past observations, we naturally obtained the variance of the predictive distribution of the future output, which enabled us to estimate MVLB as well as estimation uncertainty. Also, an advantage of the proposed method over others is its ability to estimate MVLB recursively. The application of this method to the real-life dynamic process (e

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Huang, Yu-Lun, Jaehun Jung, Colin M. S. Mulligan, Jaekeun Oh, and Marc F. Norcross. "A Majority of Anterior Cruciate Ligament Injuries Can Be Prevented by Injury Prevention Programs: A Systematic Review of Randomized Controlled Trials and Cluster–Randomized Controlled Trials With Meta-analysis." American Journal of Sports Medicine 48, no. 6 (2019): 1505–15. http://dx.doi.org/10.1177/0363546519870175.

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Background: Anterior cruciate ligament (ACL) injury prevention programs (IPPs) are generally accepted as being valuable for reducing injury risk. However, significant methodological limitations of previous meta-analyses raise questions about the efficacy of these programs and the extent to which meeting current best-practice ACL IPP recommendations influences the protective effect of these programs. Purpose: To (1) estimate the protective effect of ACL IPPs while controlling for common methodological limitations of previous meta-analyses and (2) systematically categorize IPP components and fac

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Dai, Zhi Hua, Yu An Pan, and Jie Yao. "Parameters Recursive Identification of Minimum Variance Control." Applied Mechanics and Materials 347-350 (August 2013): 15–18. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.15.

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we discuss the problem of parameters recursive identification and designing of optimal input signal for minimum variance control from the point of system identification. we propose multi-innovation recursive least-squares identification method and separable iterative recursive least-squares identification method to identify and estimate it on line. Finally, the efficiency and possibility of the proposed strategy can be confirmed by the simulation example results.

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Narita, Yasuhito, Yoshihiro Nishimura, and Tohru Hada. "Minimum variance projection for direct measurements of power-law spectra in the wavenumber domain." Annales Geophysicae 35, no. 3 (2017): 639–44. http://dx.doi.org/10.5194/angeo-35-639-2017.

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Abstract. Minimum variance projection is widely used in geophysical and space plasma measurements to identify the wave propagation direction and the wavenumber of the wave fields. The advantage of the minimum variance projection is its ability to estimate the energy spectra directly in the wavenumber domain using only a limited number of spatial samplings. While the minimum variance projection is constructed for discrete signals in the data, we find that the minimum variance projection can reasonably reproduce the spectral slope of the power-law spectrum if the data represent continuous power-

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Rubesam, Alexandre, and André Lomonaco Beltrame. "Carteiras de Variância Mínima no Brasil." Brazilian Review of Finance 11, no. 1 (2013): 81. http://dx.doi.org/10.12660/rbfin.v11n1.2013.5830.

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We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i) the IBOVESPA equity index, (ii) an equally-weighted portfolio, (iii) the maximum Sharpe ratio portfolio and (iv) the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long

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11

Cherubini, Giacomo. "Almost periodic functions and hyperbolic counting." International Journal of Number Theory 14, no. 09 (2018): 2343–68. http://dx.doi.org/10.1142/s1793042118501439.

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We prove the existence of asymptotic moments and an estimate on the tails of the limiting distribution for a specific class of almost periodic functions. Then we introduce the hyperbolic circle problem, proving an estimate on the asymptotic variance of the remainder that improves a result of Chamizo. Applying the results of the first part we prove the existence of limiting distribution and asymptotic moments for three functions that are integrated versions of the remainder, and were considered originally (with due adaptations to our settings) by Wolfe, Phillips and Rudnick, and Hill and Parnov

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AL-Mouel, Abdulhussein Saber, and Jasim Mohammed Ali. "Best Quadratic unbiased Estimator for Variance Component of One-Way Repeated Measurement Model." JOURNAL OF ADVANCES IN MATHEMATICS 14, no. 1 (2018): 7615–23. http://dx.doi.org/10.24297/jam.v14i1.7342.

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The studies of analysis of variance components is one of the important topics in mathematical statistics for this subject of wide application. In this paper given best quadratic unbiased estimator of variance components for balanced data for linear one-way repeated measurement model (RMM). We computed the quadratic unbiased estimator, which has minimum variance (best quadratic unbiased estimate (BQUE)) by using analysis of variance (ANOVA) method of estimating the variance components.

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Thanoon, Shaymaa Riyadh. "A comparison between Bayes estimation and the estimation of the minimal unbiased quadratic Standard of the bi-division variance analysis model in the presence of interaction." Tikrit Journal of Pure Science 25, no. 2 (2020): 116. http://dx.doi.org/10.25130/j.v25i2.966.

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In this study, the variance compounds parameters of the mixed bi-division variance analysis sample are estimated. This estimation is obtained, by Bayes quadratic unbiased estimator. The second way to estimate variance compounds parameters of a suggested tow-way analysis of variance mixed model with interaction. estimation is done out by the approach called (MINQUÉ). The estimation approach is conducted on true obtained from departments at the college of agriculture/university of Mosul. These data represent the development of growing various kinds of tomato so that the development represents th

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14

Chan, Ngai Hang. "On the Noninvertible Moving Average Time Series with Infinite Variance." Econometric Theory 9, no. 4 (1993): 680–85. http://dx.doi.org/10.1017/s0266466600008057.

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The limiting distribution of the least squares estimate of the derived process of a noninvertible and nearly noninvertible moving average model with infinite variance innovations is established as a functional of a Lévy process. The form of the limiting law depends on the initial value of the innovation and the stable index α. This result enables one to perform asymptotic testing for the presence of a unit root for a noninvertible moving average model through the constructed derived process under the null hypothesis. It provides not only a parallel analog of its autoregressive counterparts, bu

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15

Bishop, Craig H., Elizabeth A. Satterfield, and Kevin T. Shanley. "Hidden Error Variance Theory. Part II: An Instrument That Reveals Hidden Error Variance Distributions from Ensemble Forecasts and Observations." Monthly Weather Review 141, no. 5 (2013): 1469–83. http://dx.doi.org/10.1175/mwr-d-12-00119.1.

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Abstract In Part I of this study, a model of the distribution of true error variances given an ensemble variance is shown to be defined by six parameters that also determine the optimal weights for the static and flow-dependent parts of hybrid error variance models. Two of the six parameters (the climatological mean of forecast error variance and the climatological minimum of ensemble variance) are straightforward to estimate. The other four parameters are (i) the variance of the climatological distribution of the true conditional error variances, (ii) the climatological minimum of the true co

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Shi, Yi Ran, Yan Tao Tian, Lan Xiang Zhu, and Li Fei Deng. "The MUSIC Minimum Norm Method for Linear Polarized Array Parameter Estimation." Applied Mechanics and Materials 411-414 (September 2013): 1559–63. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1559.

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This paper used signal Cyclostationarity and MUSIC minimum norm method to estimate DOA and polarization parameters with linear polarization array. Cyclostationarity statistics have the advantage of limiting different frequencies of signal cycle stationary colored noise and inhibit both the minimum norm loop correlation function and estimation error. This paper also verifies the effectiveness of the method through simulation experiments.

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17

Liu, Xiaofeng, and Stephen Raudenbush. "A Note on the Noncentrality Parameter and Effect Size Estimates for the F Test in ANOVA." Journal of Educational and Behavioral Statistics 29, no. 2 (2004): 251–55. http://dx.doi.org/10.3102/10769986029002251.

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The noncentrality parameter for the noncentral F is a precision-weighted sum of squares of treatment means, which is closely related to the test statistic and effect size. The two common effect size estimates are not based on the uniformly minimum variance unbiased (UMVU) estimate of the noncentrality parameter. The UMVU estimate of the noncentrality parameter implies a new and more conservative effect size estimate.

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18

Zhao, Juan, and Yunmin Zhu. "New results about the relationship between optimally weighted least squares estimate and linear minimum variance estimate." Journal of Systems Science and Complexity 22, no. 1 (2009): 137–49. http://dx.doi.org/10.1007/s11424-009-9152-z.

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19

Hasegawa, Hideyuki, and Ryo Nagaoka. "Improvement of performance of minimum variance beamformer by introducing cross covariance estimate." Journal of Medical Ultrasonics 47, no. 2 (2020): 203–10. http://dx.doi.org/10.1007/s10396-020-01009-7.

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20

Balandin, Dmitry V. "Limiting Vibroisolation Control of an Oscillating String on a Moving Base." Shock and Vibration 2, no. 2 (1995): 163–71. http://dx.doi.org/10.1155/1995/203067.

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The vibroisolating capability of an elastic object that is assumed to be protected against a class of excitations is studied. It is proposed that this capability be estimated by a quadratic functional. The solution method gives an estimate of the optimal isolation with a criterion of minimum guaranteed quality. A numerical example of the solution technique is presented.

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Shrestha, Keshab, Sheena Sara Suresh Philip, and Yessy Peranginangin. "Contribution of Exchange Traded Funds in Hedging Crude Oil Price Risk." American Business Review 26, no. 1 (2023): 203–25. http://dx.doi.org/10.37625/abr.26.1.203-225.

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In this study, we empirically analyze the contributions of three crude oil-based exchange traded funds (ETFs) and the futures contract in hedging crude oil price risk. In order to measure hedging contributions of ETFs, we estimate the usual minimum variance hedge ratios as well as the quantile based minimum variance hedge ratios based on three different methods. We also compute the hedging effectiveness of the futures contract and three ETFs. We find that ETFs can be used as hedging instruments especially for the longer hedging horizons and extreme quantiles. However, overall, we find the futu

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López-Herrera, Francisco, Roberto Santillán-Salgado, and Edgar Ortiz. "Interdependence of NAFTA capital markets: A minimum variance portfolio approach." Panoeconomicus 61, no. 6 (2014): 691–707. http://dx.doi.org/10.2298/pan1406691l.

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We estimate the long-run relationships among NAFTA capital market returns and then calculate the weights of a ?time-varying minimum variance portfolio? that includes the Canadian, Mexican, and USA capital markets between March 2007 and March 2009, a period of intense turbulence in international markets. Our results suggest that the behavior of NAFTA market investors is not consistent with that of a theoretical ?risk-averse? agent during periods of high uncertainty and may be either considered as irrational or attributed to a possible ?home country bias?. This finding represents valuable inform

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23

Kunze, Julius, Louis Kirsch, Hippolyt Ritter, and David Barber. "Gaussian Mean Field Regularizes by Limiting Learned Information." Entropy 21, no. 8 (2019): 758. http://dx.doi.org/10.3390/e21080758.

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Variational inference with a factorized Gaussian posterior estimate is a widely-used approach for learning parameters and hidden variables. Empirically, a regularizing effect can be observed that is poorly understood. In this work, we show how mean field inference improves generalization by limiting mutual information between learned parameters and the data through noise. We quantify a maximum capacity when the posterior variance is either fixed or learned and connect it to generalization error, even when the KL-divergence in the objective is scaled by a constant. Our experiments suggest that

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Ahmad, Ahmad. "On The Problem of the Estimation of Variance Components Based On Non-linear Maximization Approach." Neutrosophic and Information Fusion 3, no. 1 (2024): 27–33. http://dx.doi.org/10.54216/nif.030104.

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In this paper, we study the problem of estimating variance components in the two-way classification with interaction in the random effect linear model by non-linear maximization. We assume the model according to the assumptions and give the theory of derivation of the estimators of these components, then apply these estimators on real data and obtain the estimates. We estimate these components by two other methods: the solution of the expected equation of mean square in the analysis of the variance table, and the minimum variance quadratic unbiased estimator.

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Batra, Deepak, Sanjay Sharma, and Amit Kumar Kohli. "Improved Parameter Estimation for First-Order Markov Process." Research Letters in Signal Processing 2009 (2009): 1–2. http://dx.doi.org/10.1155/2009/186250.

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This correspondence presents a linear transformation, which is used to estimate correlation coefficient of first-order Markov process. It outperforms zero-forcing (ZF), minimum mean-squared error (MMSE), and whitened least-squares (WTLSs) estimators by controlling output noise variance at the cost of increased computational complexity.

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Lee, Chanhwa. "Observability Decomposition-Based Decentralized Kalman Filter and Its Application to Resilient State Estimation under Sensor Attacks." Sensors 22, no. 18 (2022): 6909. http://dx.doi.org/10.3390/s22186909.

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This paper considers a discrete-time linear time invariant system in the presence of Gaussian disturbances/noises and sparse sensor attacks. First, we propose an optimal decentralized multi-sensor information fusion Kalman filter based on the observability decomposition when there is no sensor attack. The proposed decentralized Kalman filter deploys a bank of local observers who utilize their own single sensor information and generate the state estimate for the observable subspace. In the absence of an attack, the state estimate achieves the minimum variance, and the computational process does

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Lu, Zihao, Na Wang, and Shigui Dong. "Improved Square-Root Cubature Kalman Filtering Algorithm for Nonlinear Systems with Dual Unknown Inputs." Mathematics 12, no. 1 (2023): 99. http://dx.doi.org/10.3390/math12010099.

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For nonlinear discrete systems with dual unknown inputs, there are many limitations regarding previous nonlinear filters. This paper proposes two new, improved square-root cubature Kalman filtering (ISRCKF) algorithms to estimate system states and dual unknown inputs. Improved square-root cubature Kalman filtering 1 (ISRCKF1) introduces an innovation that first obtains the unknown input estimates from the measurement equation, then updates the innovation to derive the unknown input estimates from the state equation, then uses the already obtained estimates of the dual unknown inputs to correct

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Zibri, Arben, and Agim Kukeli. "Does GMVP Strategy Reduce Risk? A Global Asset Approach." Journal of Applied Business Research (JABR) 30, no. 6 (2014): 1873. http://dx.doi.org/10.19030/jabr.v30i6.8899.

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<p>This paper studies the out of sample risk reduction of global minimum variance portfolio. The analysis are drown from the discussions of Jagannathan and Ma (2003) regarding the risk reduction in US stock portfolios using portfolio constraints. We estimate the covariance matrix using the sample covariance matrix approach and derive optimal minimum variance portfolios considering upper/lower bounds and no restrictions. Results are shown under different revision frequency and transaction costs assumed. The data used are monthly indices of stocks, bonds, gold oil and spreads from 1996 unt

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Cattaneo, Matias D., Michael Jansson, and Whitney K. Newey. "ALTERNATIVE ASYMPTOTICS AND THE PARTIALLY LINEAR MODEL WITH MANY REGRESSORS." Econometric Theory 34, no. 2 (2016): 277–301. http://dx.doi.org/10.1017/s026646661600013x.

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Many empirical studies estimate the structural effect of some variable on an outcome of interest while allowing for many covariates. We present inference methods that account for many covariates. The methods are based on asymptotics where the number of covariates grows as fast as the sample size. We find a limiting normal distribution with variance that is larger than the standard one. We also find that with homoskedasticity this larger variance can be accounted for by using degrees-of-freedom-adjusted standard errors. We link this asymptotic theory to previous results for many instruments and

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Gope, Prakash Chandra. "Determination of Minimum Number of Specimens in S-N Testing." Journal of Engineering Materials and Technology 124, no. 4 (2002): 421–27. http://dx.doi.org/10.1115/1.1417486.

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A method for determination of minimum sample size required to estimate the fatigue life has been presented. No functional relationship between stress and fatigue life other than log normal and Weibull distribution function of fatigue life has been assumed. The method is based on the analysis of the variance of error which arises due to scattered nature of the fatigue life data. An example of the application of the presented method is also given.

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Rajabi, Mahdi, Patrick Gerard, and Jennifer Ogle. "Highway Safety Manual Calibration: Estimating the Minimum Required Sample Size." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 4 (2021): 510–23. http://dx.doi.org/10.1177/03611981211062219.

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Crash frequency has been identified by many experts as one of the most important safety measures, and the Highway Safety Manual (HSM) encompasses the most commonly accepted predictive models for predicting the crash frequency on specific road segments and intersections. The HSM recommends that the models be calibrated using data from a jurisdiction where the models will be applied. One of the most common start-up issues with the calibration process is how to estimate the required sample size to achieve a specific level of precision, which can be a function of the variance of the calibration fa

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Khan, Rasul A. "A note on Hammersley's inequality for estimating the normal integer mean." International Journal of Mathematics and Mathematical Sciences 2003, no. 34 (2003): 2147–56. http://dx.doi.org/10.1155/s016117120320822x.

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LetX1,X2,…,Xnbe a random sample from a normalN(θ,σ2)distribution with an unknown meanθ=0,±1,±2,…. Hammersley (1950) proposed the maximum likelihood estimator (MLE)d=[X¯n], nearest integer to the sample mean, as an unbiased estimator ofθand extended the Cramér-Rao inequality. The Hammersley lower bound for the variance of any unbiased estimator ofθis significantly improved, and the asymptotic (asn→∞) limit of Fraser-Guttman-Bhattacharyya bounds is also determined. A limiting property of a suitable distance is used to give some plausible explanations why such bounds cannot be attained. An almost

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RAMIREZ-MARQUEZ, JOSE E., DAVID W. COIT, and TONGDAN JIN. "TEST PLAN ALLOCATION TO MINIMIZE SYSTEM RELIABILITY ESTIMATION VARIABILITY." International Journal of Reliability, Quality and Safety Engineering 11, no. 03 (2004): 257–72. http://dx.doi.org/10.1142/s0218539304001506.

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A new methodology is presented to allocate testing units to the different components within a system when the system configuration is fixed and there are budgetary constraints limiting the amount of testing. The objective is to allocate additional testing units so that the variance of the system reliability estimate, at the conclusion of testing, will be minimized. Testing at the component-level decreases the variance of the component reliability estimate, which then decreases the system reliability estimate variance. The difficulty is to decide which components to test given the system-level

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Ma, Chenchen, and Shihong Yue. "Minimum Sample Size Estimate for Classifying Invasive Lung Adenocarcinoma." Applied Sciences 12, no. 17 (2022): 8469. http://dx.doi.org/10.3390/app12178469.

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Statistical Learning Theory (SLT) plays an important role in prediction estimation and machine learning when only limited samples are available. At present, determining how many samples are necessary under given circumstances for prediction accuracy is still an unknown. In this paper, the medical diagnosis on lung cancer is taken as an example to solve the problem. Invasive adenocarcinoma (IA) is a main type of lung cancer, often presented as ground glass nodules (GGNs) in patient’s CT images. Accurately discriminating IA from non-IA based on GGNs has important implications for taking the righ

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Dong, Shigui, Na Wang, Xueyan Wang, and Zihao Lu. "Extended Recursive Three-Step Filter for Linear Discrete-Time Systems with Dual-Unknown Inputs." Energies 16, no. 15 (2023): 5603. http://dx.doi.org/10.3390/en16155603.

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This paper proposes two new extended recursive three-step filters for linear discrete systems with dual-unknown inputs, which can simultaneously estimate unknown input and state. Extended recursive three-step filter 1 (ERTSF1) introduces an innovation for obtaining the estimates of the unknown input in the measurement equation, then derives the estimates of the unknown input in the state equation. After that, it uses the already obtained estimates of the dual-unknown inputs to correct the one-step prediction of the state, and finally, it obtains the minimum-variance unbiased estimate of the sy

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Nayak, Tapan Kumar. "Estimating the Parameter of a Selected Population." Calcutta Statistical Association Bulletin 45, no. 1-2 (1995): 93–102. http://dx.doi.org/10.1177/0008068319950105.

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Suppose independent samples from k populations with unknown parameters are taken and one of the populations is selected based on tho data and a prespecified rule. The problem is to estimate the parameter of the selected population. The estimand, G, is a random quantity which depends on both the data and the unknown parameters. While standard estimation methods are inadequate for estimating G, they can be used to estimate the expected value of G. It is shown that the uniformly minimum variance unbiased estimator of E( G) is also the uniformly minimum mean squared error unbiased estimator of G,

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Wang, Yanxue, Jiawei Xiang, Jiang Zhansi, Yang Lianfa, and Zhengjia He. "Vibration signals denoising using minimum description length principle for detecting impulsive signatures." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 10 (2013): 1818–28. http://dx.doi.org/10.1177/0954406213498544.

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Vibration signals are usually affected by noise, which is in turn related to the measurement and data processing procedures. This paper presents a new subband adaptive denoising method for detective impulsive signatures based on minimum description length principle with improved normalized maximum likelihood density model. The threshold of the proposed denoising method is determined automatically without the need to estimate the noise variance. The effectiveness of the proposed denoising method over VisuaShrink, BayesShrink and minimum description length denoising methods are given through sim

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Swanson, George D. "A Minimum Variance Estimate In The Doubly Labeled Water Technique-Role Of Optimal Sampling." Medicine & Science in Sports & Exercise 41 (May 2009): 447. http://dx.doi.org/10.1249/01.mss.0000355910.50932.c2.

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Almanofi, Anas M., Adnan Malki, and Ali Kazem. "Doppler Frequency Estimation for a Maneuvering Target Being Tracked by Passive Radar Using Particle Filter." Journal of communications software and systems 16, no. 4 (2020): 279–84. http://dx.doi.org/10.24138/jcomss.v16i4.1097.

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In this paper, we estimate Doppler frequency of a maneuvering target being tracked by passive radar using two types of particle filter, the first is “Maximum Likelihood Particle Filter” (MLPF) and the second is “Minimum Variance Particle filter” (MVPF). By simulating the passive radar system that has the bistatic geometry “Digital Video Broadcasting-Terrestrial (DVB-T) transmitter / receiver” with these two types, we can estimate the Doppler frequency of the maneuvering target and compare the simulation results for deciding which type gives better performance.

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Filip, Ioan, Florin Dragan, and Iosif Szeidert. "Considerations about Parameters Estimation into a Minimum Variance Control System." Applied Sciences 11, no. 13 (2021): 6165. http://dx.doi.org/10.3390/app11136165.

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The starting point to design a minimum variance control law consists in identifying a linearized mathematical model (valid around an operating point) of a nonlinear process, respectively the on-line estimation of the parameters of this model. This paper presents a comparative study regarding the estimation of these parameters for the case when the process operates in open-loop, respectively the process is integrated into a closed-loop system specific to a minimum variance control. The comparison is made both analytically (for the general case) and through a validation study (by simulation) par

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Xue, Huili, Kun Lin, Yin Luo, and Hongjun Liu. "Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation." Shock and Vibration 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/9301876.

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A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the w

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Tsatsaronis, Michael. "Optimal hedging efficiency in global freight markets: Comparing FFAs and time charter strategies." Maritime Technology and Research 6, no. 3 (2024): 268609. http://dx.doi.org/10.33175/mtr.2024.268609.

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The paper aims to mitigate financial risk in highly volatile shipping freight markets by employing a dynamic hedging model. The primary criterion for evaluating the effectiveness of various methods for estimating optimal hedge ratios through Forward Freight Agreements (FFAs) is the minimum variance hedging rule. Four different methods are utilized to estimate two types of hedge ratios. The first type, a static hedge ratio, is calculated using the OLS and ECM methods. The second type, a time-varying hedge ratio, is determined through a bivariate GARCH model and a Rolling Window OLS method. Addi

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Crittenden, R. N., G. L. Thomas, D. A. Marino, and R. E. Thorne. "A Weighted Duration-in-Beam Estimator for the Volume Sampled by a Quantitative Echo Sounder." Canadian Journal of Fisheries and Aquatic Sciences 45, no. 7 (1988): 1249–56. http://dx.doi.org/10.1139/f88-147.

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Estimation of absolute fish density or abundance using the echo-count technique requires estimation of the volume sampled. The unknown parameter in the volume sampled is the sine of the half-angle of the effective conical beam. We derive the minimum variance, unbiased, linear estimator of this parameter. This estimator is based upon weighted regression through the origin and reduces to a computationally simple form. We use this estimate and its variance to estimate absolute density, absolute abundance, and their variances. We use a bootstrap procedure to contrast the performance of our method

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Ng, Set Foong, Pei Eng Ch’ng, Yee Ming Chew, and Kok Shien Ng. "Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties." Scientific Research Journal 11, no. 1 (2014): 15. http://dx.doi.org/10.24191/srj.v11i1.5416.

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Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this pap

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Ng, Set Foong, Pei Eng Ch’ng, Yee Ming Chew, and Kok Shien Ng. "Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties." Scientific Research Journal 11, no. 1 (2014): 15. http://dx.doi.org/10.24191/srj.v11i1.9398.

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Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this pap

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Abaali, Mostafa, Jérôme Harmand, and Zoubida Mghazli. "Impact of Dual Substrate Limitation on Biodenitrification Modeling in Porous Media." Processes 8, no. 8 (2020): 890. http://dx.doi.org/10.3390/pr8080890.

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In this work, we consider a model of the biodenitrification process taking place in a spatially-distributed bioreactor, and we take into account the limitation of the kinetics by both the carbon source and the oxidized nitrogen. This model concerns a single type of bacteria growing on nitrate, which splits into adherent bacteria or free bacteria in the liquid, taking all interactions into account. The system obtained consists of four diffusion-convection-reaction equations for which we show the existence and uniqueness of a global solution. The system is approximated by a standard finite eleme

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Taylor, Joseph A., Terri Pigott, and Ryan Williams. "Promoting Knowledge Accumulation About Intervention Effects: Exploring Strategies for Standardizing Statistical Approaches and Effect Size Reporting." Educational Researcher 51, no. 1 (2021): 72–80. http://dx.doi.org/10.3102/0013189x211051319.

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Toward the goal of more rapid knowledge accumulation via better meta-analyses, this article explores statistical approaches intended to increase the precision and comparability of effect sizes from education research. The featured estimate of the proposed approach is a standardized mean difference effect size whose numerator is a mean difference that has been adjusted for baseline differences in the outcome measure, at a minimum, and whose denominator is the total variance. The article describes the utility and efficiency of covariate adjustment through baseline measures and the need to standa

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Lee, Hsiang-Tai, and Jonathan K. Yoder. "A bivariate Markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios." Applied Economics 39, no. 10 (2007): 1253–65. http://dx.doi.org/10.1080/00036840500438970.

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Lima, Maria A. F., Jorge O. Trierweiler, and Marcelo Farenzena. "A new approach to estimate the Minimum Variance Control law for Nonminimum phase Multivariable Systems." IFAC-PapersOnLine 52, no. 1 (2019): 886–91. http://dx.doi.org/10.1016/j.ifacol.2019.06.174.

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Habib Mahdi, Mustafa, and Saja Mohammad Hussein. "Estimating the Population Mean in Stratified Random Sampling Using Combined Regression with the Presence of Outliers." Journal of Economics and Administrative Sciences 29, no. 136 (2023): 70–80. http://dx.doi.org/10.33095/jeas.v29i136.2608.

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In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covari

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