Academic literature on the topic 'Asymptotic variance estimation'

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Journal articles on the topic "Asymptotic variance estimation"

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Joshi, S. N., and A. L. Rukhini. "Asymptotic Estimation of Variance." Theory of Probability & Its Applications 35, no. 4 (1991): 777–84. http://dx.doi.org/10.1137/1135112.

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Rukhin, Andrew L. "Asymptotic variance estimation in multivariate distributions." Journal of Multivariate Analysis 38, no. 2 (1991): 366–84. http://dx.doi.org/10.1016/0047-259x(91)90051-3.

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Chen, Liqiong, Antonio F. Galvao, and Suyong Song. "Quantile Regression with Generated Regressors." Econometrics 9, no. 2 (2021): 16. http://dx.doi.org/10.3390/econometrics9020016.

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This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of the two-step estimator, namely, consistency and asymptotic normality are established. We show that the asymptotic variance-covariance matrix needs to be adjusted to account for the first-step estimation error. We propose a general estimator for the asymptotic variance-covariance, establish its consistency, and develop testing procedures for li
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Saikkonen, Pentti. "Asymptotically Efficient Estimation of Cointegration Regressions." Econometric Theory 7, no. 1 (1991): 1–21. http://dx.doi.org/10.1017/s0266466600004217.

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An asymptotic optimality theory for the estimation of cointegration regressions is developed in this paper. The theory applies to a reasonably wide class of estimators without making any specific assumptions about the probability distribution or short-run dynamics of the data-generating process. Due to the nonstandard nature of the estimation problem, the conventional minimum variance criterion does not provide a convenient measure of asymptotic efficiency. An alternative criterion, based on the concentration or peakedness of the limiting distribution of an estimator, is therefore adopted. The
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Küchenhoff, Helmut, Wolfgang Lederer, and Emmanuel Lesaffre. "Asymptotic variance estimation for the misclassification SIMEX." Computational Statistics & Data Analysis 51, no. 12 (2007): 6197–211. http://dx.doi.org/10.1016/j.csda.2006.12.045.

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Yousef, Ali, Ayman A. Amin, Emad E. Hassan, and Hosny I. Hamdy. "Multistage Estimation of the Rayleigh Distribution Variance." Symmetry 12, no. 12 (2020): 2084. http://dx.doi.org/10.3390/sym12122084.

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In this paper we discuss the multistage sequential estimation of the variance of the Rayleigh distribution using the three-stage procedure that was presented by Hall (Ann. Stat. 9(6):1229–1238, 1981). Since the Rayleigh distribution variance is a linear function of the distribution scale parameter’s square, it suffices to estimate the Rayleigh distribution’s scale parameter’s square. We tackle two estimation problems: first, the minimum risk point estimation problem under a squared-error loss function plus linear sampling cost, and the second is a fixed-width confidence interval estimation, us
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Newey, Whitney K. "Kernel Estimation of Partial Means and a General Variance Estimator." Econometric Theory 10, no. 2 (1994): 1–21. http://dx.doi.org/10.1017/s0266466600008409.

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Econometric applications of kernel estimators are proliferating, suggesting the need for convenient variance estimates and conditions for asymptotic normality. This paper develops a general “delta-method” variance estimator for functionals of kernel estimators. Also, regularity conditions for asymptotic normality are given, along with a guide to verify them for particular estimators. The general results are applied to partial means, which are averages of kernel estimators over some of their arguments with other arguments held fixed. Partial means have econometric applications, such as consumer
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Salha, Raid B., Hazem I. El Shekh Ahmed, and Hossam O. EL-Sayed. "Adaptive Kernel Estimation of the Conditional Quantiles." International Journal of Statistics and Probability 5, no. 1 (2015): 79. http://dx.doi.org/10.5539/ijsp.v5n1p79.

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In this paper, we define the adaptive kernel estimation of the conditional distribution function (cdf) for independent and identically distributed (iid) data using varying bandwidth. The bias, variance and the mean squared error of the proposed estimator are investigated. Moreover, the asymptotic normality of the proposed estimator is investigated.<br /><br />The results of the simulation study show that the adaptive kernel estimation of the conditional quantiles with varying bandwidth have better performance than the kernel estimations with fixed bandwidth.
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Newey, Whitney K. "Series Estimation of Regression Functionals." Econometric Theory 10, no. 1 (1994): 1–28. http://dx.doi.org/10.1017/s0266466600008203.

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Two-step estimators, where the first step is the predicted value from a nonparametric regression, are useful in many contexts. Examples include a non-parametric residual variance, probit with nonparametric generated regressors, efficient GMM estimation with randomly missing data, heteroskedasticity corrected least squares, semiparametric regression, and efficient nonlinear instrumental variables estimators. The purpose of this paper is the development of consistency and asymptotic normality results when the first step is a series estimator. The paper presents the form of a correction term for
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Wang, Ji-xia, and Qing-xian Xiaob. "Local polynomial estimation of time-dependent diffusion parameter for discretely observed SDE models." Filomat 28, no. 4 (2014): 871–78. http://dx.doi.org/10.2298/fil1404871w.

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Extending the results of Yu, Yu, Wang and Lin [10], we study the local polynomial estimation of the time-dependent diffusion parameter for time-inhomogeneous diffusion models. Considering the diffusion parameter being positive, we obtain the local polynomial estimation of the diffusion parameter by taking the diffusion parameter to be local log-polynomial fitting. The asymptotic bias, asymptotic variance and asymptotic normal distribution of the volatility function are discussed. A real data analysis is conducted to show the performance of the estimations proposed.
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Dissertations / Theses on the topic "Asymptotic variance estimation"

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Sohrabi, Maryam. "On Robust Asymptotic Theory of Unstable AR(p) Processes with Infinite Variance." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34280.

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In this thesis, we explore some asymptotic results in heavy-tailed theory. There are many empirical and compelling evidence in statistics that require modeling with heavy tailed observations. This thesis is divided into three parts. First, we consider a robust estimation of the mean vector for a sequence of independent and identically distributed observations in the domain of attraction of a stable law with possibly different indices of stability between 1 and 2. The suggested estimator is asymptotically normal with unknown parameters. We apply an asymptotically valid bootstrap to const
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Hofmann, Glenn, Erhard Cramer, N. Balakrishnan, and Gerd Kunert. "An Asymptotic Approach to Progressive Censoring." Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200201539.

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Progressive Type-II censoring was introduced by Cohen (1963) and has since been the topic of much research. The question stands whether it is sensible to use this sampling plan by design, instead of regular Type-II right censoring. We introduce an asymptotic progressive censoring model, and find optimal censoring schemes for location-scale families. Our optimality criterion is the determinant of the 2x2 covariance matrix of the asymptotic best linear unbiased estimators. We present an explicit expression for this criterion, and conditions for its boundedness. By means of numerical optimization
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Ploeg, Jan van der. "Instrumental variable estimation and group-asymptotics." Capelle a/d IJssel : [Groningen] : Labyrinth Publication ; [University Library Groningen] [Host], 1997. http://irs.ub.rug.nl/ppn/157854507.

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Mint, El Mouvid Mariem. "Sur l'estimateur linéaire local de la fonction de répartition conditionnelle." Montpellier 2, 2000. http://www.theses.fr/2000MON20162.

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Dans ce travail, nous nous interessons aux aspects theoriques de l'estimateur lineaire local de la fonction de repartition conditionnelle. Dans le chapitre 1, nous faisons un rappel de la theorie des u-statistiques. Au chapitre 2, nous presentons l'estimateur sous la forme d'un rapport de deux u-statistiques dont nous determinons les principales proprietes. Dans le chapitre 3, nous etablissons sa convergence presque complete ponctuelle et uniforme. Nous etudions au chapitre 4 son erreur quadratique moyenne et nous la comparons a celles d'autres estimateurs a noyaux. Nous etablissons egalement
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Michálková, Anna. "Metoda převažování (kalibrace) ve výběrových šetřeních." Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-397804.

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In this thesis, we study re-weighting when estimating totals in survey sampling. The purpose of re-weighting is to adjust the structure of the sample in order to comply with the structure of the population (with respect to given auxiliary variables). We sum up some known results for methods of the traditional desin-based approach, more attention is given to the model-based approach. We generalize known asymptotic results in the model-based theory to a wider class of weighted estimators. Further, we propose a consistent estimator of asymptotic variance, which takes into consideration weights us
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Hoque, Ahmed. "On estimating variances for Gini coefficients with complex surveys: theory and application." Thesis, 2016. http://hdl.handle.net/1828/7582.

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Obtaining variances for the plug-in estimator of the Gini coefficient for inequality has preoccupied researchers for decades with the proposed analytic formulae often being regarded as being too cumbersome to apply, as well as usually based on the assumption of an iid structure. We examine several variance estimation techniques for a Gini coefficient estimator obtained from a complex survey, a sampling design often used to obtain sample data in inequality studies. In the first part of the dissertation, we prove that Bhattacharya’s (2007) asymptotic variance estimator when data arise from a com
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Li, Shing-Jay, and 李興傑. "On the Asymptotic Variance of the Mantel-Haenszel Estimator." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/wv3v4s.

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碩士<br>中原大學<br>應用數學研究所<br>91<br>Abstract This thesis discusses and compares several large sample variances of the Mantel-Haenszel estimator for common odds ratio calculated from a set of K 2x2 tables. The performances of these estimators are also compared with Monte Carlo results. Two large-sample models are considered,namely model I, as the number of 2x2 tables remained fixed and let the total sample size tends to infinity,and model II, as the number of marginal configuration for each 2x2 table remained finite, and let the number of tables tends to infinity. It is quite interesting that for mo
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Abarin, Taraneh. "Second-order least squares estimation in regression models with application to measurement error problems." 2009. http://hdl.handle.net/1993/3126.

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This thesis studies the Second-order Least Squares (SLS) estimation method in regression models with and without measurement error. Applications of the methodology in general quasi-likelihood and variance function models, censored models, and linear and generalized linear models are examined and strong consistency and asymptotic normality are established. To overcome the numerical difficulties of minimizing an objective function that involves multiple integrals, a simulation-based SLS estimator is used and its asymptotic properties are studied. Finite sample performances of the estimators in
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Σακελλαρίου, Ιωάννης. "Εξωτερικά-εξαρτώμενα στοχαστικά συναρτησιακά μοντέλα : μέθοδοι εκτίμησης & εφαρμογή στη διάγνωση βλαβών". 2006. http://nemertes.lis.upatras.gr/jspui/handle/10889/281.

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Ο στόχος της παρούσας διατριβής είναι η ανάπτυξη μιας νέας κλάσης εξωτερικά εξαρτώμενων στοχαστικών συναρτησιακών μοντέλων για την αναγνώριση (identification) δυναμικών συστημάτων που παρουσιάζουν πολλαπλά σημεία λειτουργίας, τα οποία καθορίζονται από μετρήσιμη εξωτερική μεταβλητή (όπως για παράδειγμα, η θερμοκρασία, η υγρασία, κ.λ.π.). Επιπλέον, στόχος είναι η ανάπτυξη καινοτόμου μεθοδολογίας διάγνωσης (ανίχνευσης, προσδιορισμού και εκτίμησης) βλαβών σε δυναμικά συστήματα βάσει των στοχαστικών συναρτησιακών μοντέλων. Η διατριβή αρχικά πραγματεύεται την ανάπτυξη κατάλληλης μεθοδολογίας που αντ
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Books on the topic "Asymptotic variance estimation"

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Keen, K. J. Asymptotic variance of the interclass correlation coefficient. University of Toronto, Department of Statistics, 1989.

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Cheng, Russell. Standard Asymptotic Theory. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0003.

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This book relies on maximum likelihood (ML) estimation of parameters. Asymptotic theory assumes regularity conditions hold when the ML estimator is consistent. Typically an additional third derivative condition is assumed to ensure that the ML estimator is also asymptotically normally distributed. Standard asymptotic results that then hold are summarized in this chapter; for example, the asymptotic variance of the ML estimator is then given by the Fisher information formula, and the log-likelihood ratio, the Wald and the score statistics for testing the statistical significance of parameter es
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Mathematical Statistics: Theory and Applications. De Gruyter, 2020.

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Book chapters on the topic "Asymptotic variance estimation"

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Gefeller, Olaf, and Franz Woltering. "Asymptotic Variance Estimation of Association Measures: A New Approach to Overcome Computational Problems." In Medical Informatics Europe 1991. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-93503-9_177.

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Alzghool, Raed. "ARCH and GARCH Models: Quasi-Likelihood and Asymptotic Quasi-Likelihood Approaches." In Linear and Non-Linear Financial Econometrics -Theory and Practice [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93726.

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This chapter considers estimation of autoregressive conditional heteroscedasticity (ARCH) and the generalized autoregressive conditional heteroscedasticity (GARCH) models using quasi-likelihood (QL) and asymptotic quasi-likelihood (AQL) approaches. The QL and AQL estimation methods for the estimation of unknown parameters in ARCH and GARCH models are developed. Distribution assumptions are not required of ARCH and GARCH processes by QL method. Nevertheless, the QL technique assumes knowing the first two moments of the process. However, the AQL estimation procedure is suggested when the conditional variance of process is unknown. The AQL estimation substitutes the variance and covariance by kernel estimation in QL. Reports of simulation outcomes, numerical cases, and applications of the methods to daily exchange rate series and weekly prices’ changes of crude oil are presented.
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Akahira, Masafumi, and Kei Takeuchi. "SECOND ORDER ASYMPTOTIC EFFICIENCY IN TERMS OF THE ASYMPTOTIC VARIANCE OF SEQUENTIAL ESTIMATION PROCEDURES IN THE PRESENCE OF NUISANCE PARAMETERS." In Joint Statistical Papers of Akahira and Takeuchi. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812791221_0034.

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"4 Estimating the Variance of the Latent Process." In Asymptotics, Nonparametrics, and Time Series. CRC Press, 1999. http://dx.doi.org/10.1201/9781482269772-22.

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"The bootstrap estimator for the asymptotic variance of (/-quantiles." In Exploring Stochastic Laws. De Gruyter, 1995. http://dx.doi.org/10.1515/9783112318768-045.

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TAKEUCHI, Kei, and Masafumi AKAHIRA. "SECOND ORDER ASYMPTOTIC EFFICIENCY IN TERMS OF ASYMPTOTIC VARIANCES OF THE SEQUENTIAL MAXIMUM LIKELIHOOD ESTIMATION PROCEDURES." In Joint Statistical Papers of Akahira and Takeuchi. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812791221_0027.

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Aïıt-Sahalia, Yacine, and Jean Jacod. "High-Frequency Observations: Identifiability and Asymptotic Efficiency." In High-Frequency Financial Econometrics. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691161433.003.0005.

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This chapter starts with a brief reminder about a number of concepts and results which pertain to classical statistical models, without specific reference to stochastic processes. It then introduces a general notion of identifiability for a parameter, in a semi-parametric setting. A parameter can be a number (or a vector), as in classical statistics; it can also be a random variable, such as the integrated volatility. The analysis is first conducted for Lévy processes, because in this case parameters are naturally non-random, and then extended to the more general situation of semimartingales. It also considers the problem of testing a hypothesis which is “random,” such as testing whether a discretely observed path is continuous or discontinuous: the null and alternative are not the usual disjoint subsets of a parameter space, but rather two disjoint subsets of the sample space, which leads to an ad hoc definition of the level, or asymptotic level, of a test in such a context. Finally, the chapter returns to the question of efficient estimation of a parameter, which is mainly analyzed from the viewpoint of “Fisher efficiency.”
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"Guidance FDA (2001) using a REML UN model. Then, this estimate is asymptotically normally distributed, unbiased with E[νˆ ] = δ +σ − (σ )− 0.04(c ) and has variance of Var[νˆ ] = 4σ δ + l + 2l − 2l + 2l To assess PBE we ‘plug-in’ estimates of δ and the variance components and calculate the upper bound of an asymptotic 90% confidence interval. If this upper bound is below zero we declare that PBE has been shown. Using the code in Appendix B and the data in Section 7.4, we obtain the value −0.24 for log(AUC) and the value −0.19 for log(Cmax). As both of these are below zero, we can declare that T and R are PBE. 7.6 ABE for a replicate design Although ABE can be assessed using a 2× 2 design, it can also be as-sessed using a replicate design. If a replicate design is used the number of subjects can be reduced to up to half that required for a 2 × 2 de-sign. In addition it permits the estimation of σ and σ . The SAS code to assess ABE for a replicate design is given in Appendix B. Using the data from Section 7.4, the 90% confidence interval for µ is (−0.1697,−0.0155) for log(AUC) and (−0.2474,−0.0505) for log(Cmax). Exponentiating the limits to obtain confidence limits for exp(µ ), gives (0.8439,0.9846) for AUC and (0.7808,0.9508) for Cmax. Only the first of these intervals is contained within the limits of 0.8 to 1.25, there-fore T cannot be considered average bioequivalent to R. To calculate the power for a replicate design with four periods and with a total of n subjects we can still use the SAS code given in Section 7.3, if we alter the formula for the variance of a difference of two obser-vations from the same subject. This will now be σ +σ instead of σ , where σ is the subject-by-formulation interaction. Note the use of σ rather than 2σ as used in the RT/TR design. This is a result of the estimator using the average of two measurements on each treatment on each subject. One advantage of using a replicate design is that the number of sub-jects needed can be much smaller than that needed for a 2×2 design. As an example, suppose that σ = 0, and we take σ = 0.355 and α = 0.05, as done in Section 7.3. Then a power of 90.5% can be achieved with only 30 subjects, which is about half the number (58) needed for the 2 × 2 design." In Design and Analysis of Cross-Over Trials. Chapman and Hall/CRC, 2003. http://dx.doi.org/10.1201/9781420036091-25.

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"strate IBE the upper bound of a 90% confidence interval for the above aggregate metric must fall below 2.49. The required upper bound can be calculated in at least three different ways: (1) method-of-moments estimation with a Cornish-Fisher approx-imation (Hyslop et al., 2000; FDA Guidance, 2001), (2) bootstrapping (FDA Guidance, 1997), and (3) by asymptotic approximations to the mean and variance of ν and ν (Patterson, 2003; Patterson and Jones, 2002b,c). Method (1) derives from theory that assumes the inde-pendence of chi-squared variables and is more appropriate to the analysis of a parallel group design. Hence it does not fully account for the within-subject correlation that is present in data obtained from cross-over tri-als. Moreover, the approach is potentially sensitive to bias introduced by missing data and imbalance in the study data (Patterson and Jones, 2002c). Method (2), which uses the nonparametric percentile bootstrap method (Efron and Tibshirani, 1993), was the earliest suggested method of calculating the upper bound (FDA Guidance, 1997), but it has sev-eral disadvantages. Among these are that it is computationally intensive and it introduces randomness into the final calculated upper bound. Re-cent modifications to ensure consistency of the bootstrap (Shao et al., 2000) do not appear to protect the Type I error rate (Patterson and Jones, 2002c) around the mixed-scaling cut-off (0.04) unless calibration (Efron and Tibshirani, 1993) is used. Use of such a calibration technique is questionable if one is making a regulatory submission. Hence, we pre-fer to use method (3) and will illustrate its use shortly. We note that this method appears to protect against inflation of the Type I error rate in IBE and PBE testing, and the use of REML ensures unbiased esti-mates (Patterson and Jones, 2002c) in data sets with missing data and imbalance, a common occurrence in cross-over designs, (Patterson and Jones, 2002a,b). In general (Patterson and Jones, 2002a), cross-over tri-als that have been used to test for IBE and PBE have used sample sizes in excess of 20 to 30 subjects, so asymptotic testing is not unreasonable, and there is a precedent for the use of such procedures in the study of pharmacokinetics (Machado et al., 1999). We present findings here based on asymptotic normal theory using REML and not taking into account shrinkage (Patterson and Jones, 2002b,c). It is possible to account for this factor using the approach of Harville and Jeske (1992); see also Ken-ward and Roger (1997). However, this approach is not considered here in the interests of space and as the approach described below appears to control the Type I error rate for sample sizes as low as 16 (Patterson and Jones, 2002c). In a 2 × 2 cross-over trial it is not possible to estimate separately the within-and between-subject variances and hence a replicate design, where subjects receiving each formulation more than once is required." In Design and Analysis of Cross-Over Trials. Chapman and Hall/CRC, 2003. http://dx.doi.org/10.1201/9781420036091-19.

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Conference papers on the topic "Asymptotic variance estimation"

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Anand, G. V., P. V. Nagesha, Sanjeev Gurugopinath, and N. Kalyanasundaram. "Sparse Asymptotic Minimum Variance Bearing Estimation of Underwater Acoustic Sources." In Global Oceans 2020: Singapore - U.S. Gulf Coast. IEEE, 2020. http://dx.doi.org/10.1109/ieeeconf38699.2020.9389304.

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Dai, Zhiyong, Yanan Qiu, Jianwei Li, and Chao Zhang. "Global asymptotic estimation of grid voltage parameters for variable frequency AC systems." In IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2017. http://dx.doi.org/10.1109/iecon.2017.8216712.

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Balashov, Dmitri, and Horst Irretier. "Maximum Response of a Slow-Variant Mechanical System During Transition Through a Resonance." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8287.

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Abstract A new approach to the estimation of the maximum transient response of a mechanical system with slow-variant natural frequencies and linear viscous damping is worked out. Based on the modal decomposition, the vibration response of a system is modeled using a set of simple vibrators with slow-variant natural frequencies. The passage through a resonance which is induced by a sweep of the excitation frequency during run-up or run-down is studied. Exact asymptotic formulas for the maximum transient response and the corresponding excitation frequency are derived analytically, starting from
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Xiong, Haoyi, Wei Cheng, Yanjie Fu, Wenqing Hu, Jiang Bian, and Zhishan Guo. "De-biasing Covariance-Regularized Discriminant Analysis." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/401.

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Fisher's Linear Discriminant Analysis (FLD) is a well-known technique for linear classification, feature extraction and dimension reduction. The empirical FLD relies on two key estimations from the data -- the mean vector for each class and the (inverse) covariance matrix. To improve the accuracy of FLD under the High Dimension Low Sample Size (HDLSS) settings, Covariance-Regularized FLD (CRLD) has been proposed to use shrunken covariance estimators, such as Graphical Lasso, to strike a balance between biases and variances. Though CRLD could obtain better classification accuracy, it usually in
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Mackay, Ed B. L., and Philip Jonathan. "Estimation of Environmental Contours Using a Block Resampling Method." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18308.

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Abstract A new method for estimating joint distributions of environmental variables is presented. The key difference to previous methods is that the joint distribution of only storm-peak parameters is modelled, rather than fitting a model to all observations. This provides a stronger justification for the use of asymptotic extreme value models, as the data considered are approximately independent. The joint distribution of all data is recovered by resampling and rescaling storm histories, conditional on the peak values. This simplifies the analysis as much of the complex dependence structure i
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Hahn, Jin-Oh, Andrew T. Reisner, and H. Harry Asada. "Identification of Multi-Channel Cardiovascular System Using Dual-Pole Laguerre Basis Functions for Assessment of Aortic Flow and TPR." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41186.

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This paper presents a novel method to identify the multichannel cardiovascular system using two distinct peripheral blood pressure signals. The method can characterize the distinct arterial path dynamics that shape each of the blood pressure signals, and recover the common aortic flow signal fed to them. A Laguerre series data compression technique is used to obtain a compact representation of the cardiovascular system, whose coefficients are identified using the multi-channel blind system identification. A Laguerre model de-convolution algorithm is developed to stably recover the aortic flow
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Cruz, Hector L. "Estimating Cooling Towers for Power Plant Applications." In ASME 2006 Power Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/power2006-88191.

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It has always been difficult to estimate size and cost of well designed counterflow induced-draught cooling towers due to the interrelationship of approach temperature and cooling range associated with each design. Attempts to estimate the cost of a tower by assessing currency per cell, per square foot, per gallon, or currency per other single metric, have never been sufficiently accurate due to the asymptotic nature of the approach temperature versus the tower size arithmetic function. To determine accurate qualitative metrics for cooling tower estimating purposes requires assessing two-varia
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Moelling, David, James Malloy, Marc Graham, Mark Taylor, and Andreas Fabricius. "Design Factors for Avoiding FAC Erosion in HRSG Low Pressure Evaporators." In ASME 2013 Power Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/power2013-98213.

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Two types of flow-driven wear phenomena are a frequent source of failures in Heat Recovery Steam Generators (HRSGs): Flow-Accelerated Corrosion (FAC) and Liquid-Droplet Impingement (LDI). The two mechanisms combined are also known by an older term, erosion-corrosion. This better describes what can be viewed as a continuum of mechanisms, driven by chemistry and/or fluid velocity, which lead to wear and consequent thinning of pipe walls. One common failure location in the HRSG is in Low Pressure (LP) Evaporator circuits, both in regions with two-phase and with single-phase flow conditions. Repla
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Reports on the topic "Asymptotic variance estimation"

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Honore, Bo E., and Louija Hu. Easy Bootstrap-Like Estimation of Asymptotic Variances. Federal Reserve Bank of Chicago, 2018. http://dx.doi.org/10.21033/wp-2018-11.

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Glynn, Peter W., and Ward Whitt. Estimating the Asymptotic Variance with Batch Means. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada228293.

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Kott, Phillip S. The Degrees of Freedom of a Variance Estimator in a Probability Sample. RTI Press, 2020. http://dx.doi.org/10.3768/rtipress.2020.mr.0043.2008.

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Inferences from probability-sampling theory (more commonly called “design-based sampling theory”) often rely on the asymptotic normality of nearly unbiased estimators. When constructing a two-sided confidence interval for a mean, the ad hoc practice of determining the degrees of freedom of a probability-sampling variance estimator by subtracting the number of its variance strata from the number of variance primary sampling units (PSUs) can be justified by making usually untenable assumptions about the PSUs. We will investigate the effectiveness of this conventional and an alternative method fo
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Hahn, Jinyong, Xiaohong Chen, and Daniel Ackerberg. A practical asymptotic variance estimator for two-step semiparametric estimators. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.2211.

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