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Books on the topic 'Estimation theory. Bayesian statistical decision theory. Prediction theory'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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1

Large-scale inference: Empirical Bayes methods for estimation, testing, and prediction. Cambridge University Press, 2010.

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2

Guttman, Irwin. Bayesian estimation in two-way tables with heterogeneous variances. University of Toronto, Dept. of Statistics, 1987.

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3

Samaniego, Francisco J. A comparison of the Bayesian and frequentist approaches to estimation. Springer, 2010.

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4

Bayesian inference: Parameter estimation and decisions. Springer, 2003.

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5

Bayesian spectrum analysis and parameter estimation. Springer-Verlag, 1988.

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6

Grycko, Eugen. Zur Bayesschen Theorie mengenwertiger Entscheidungsfunktionen. A. Hain, 1993.

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7

Pilz, Jürgen. Bayesian estimation and experimental design in linear regression models. 2nd ed. Wiley, 1991.

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8

Guttman, Irving. Prediction in circular distributions. University of Toronto, Dept. of Statistics, 1989.

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9

Męczarski, Marek. Problemy odporności w bayesowskiej analizie statystycznej. Szkoła Główna Handlowa, 1998.

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10

Press, S. James. Empirical Bayes estimation of the mean in a multivariate normal distribution. Rand, 1986.

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11

Harney, Hanns L. Bayesian inference: Parameter estimation and decisions. Springer, 2002.

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12

Haug, Anton J. Bayesian estimation and tracking: A practical guide. Wiley, 2012.

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13

1933-, Smith C. Ray, and Erickson Gary J, eds. Maximum-entropy and Bayesian spectral analysis and estimation problems: Proceedings of the Third Workshop on Maximum Entropy and Bayesian Methods in Applied Statistics, Wyoming, U.S.A., August 1-4, 1983. D. Reidel Pub. Co., 1987.

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14

Financial risk management with Bayesian estimation of GARCH models: Theory and applications. Springer, 2008.

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15

Recursive nonlinear estimation: A geometric approach. Springer, 1996.

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16

Savchuk, V. P. Bayesian methods for statistical estimation with application to reliability. World Federation Publishers, 1996.

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17

Saleh, A. K. Md. Ehsanes. Theory of Preliminary Test and Stein-Type Estimation with Applications. John Wiley & Sons, Ltd., 2006.

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18

Sung, Li-kang. Changing sources of international comparative advantage: A Bayesian estimation of the trade dependence model. Research School of Pacific and Asian Studies, the Australian National University, 1994.

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19

Reiser, Benjamin. A comparison of three point estimators for P(Y. University of Toronto, Dept. of Statistics, 1985.

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20

Pilz, Jürgen. Bayesian estimation and experimental design in linear regression models. Wiley, 1991.

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21

Largescale Inference Empirical Bayes Methods For Estimation Testing And Prediction. Cambridge University Press, 2013.

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22

Zellner, Arnold, Jack C. Lee, and Wesley O. Johnson. Modelling and Prediction Honoring Seymour Geisser. Springer, 2012.

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23

Samaniego, Francisco J. A Comparison of the Bayesian and Frequentist Approaches to Estimation. Springer, 2012.

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24

Bretthorst, G. Larry. Bayesian Spectrum Analysis and Parameter Estimation. Springer, 2013.

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25

Reid, N., and S. E. Ahmed. Empirical Bayes and Likelihood Inference. Springer, 2011.

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26

(Editor), S. E. Ahmed, and N. Reid (Editor), eds. Empirical Bayes and Likelihood Inference. Springer, 2000.

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27

Garre, Francisca. Issues In The Estimation And Testing Of Methods For Cat Data. Purdue University Press, 2005.

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28

Jazwinski, Andrew H. Stochastic Processes and Filtering Theory. Dover Publications, 2007.

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29

(Editor), Jack C. Lee, Wesley O. Johnson (Editor), and Arnold Zellner (Editor), eds. Modelling and Prediction: Honoring Seymour Geisser. Springer, 1996.

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30

Lin, Lie-fen. Uses of Bayesian posterior modes in solving complex estimation problems in statistics. 1992.

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31

Phadia, Eswar G. Prior Processes and Their Applications: Nonparametric Bayesian Estimation. Springer, 2018.

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32

Phadia, Eswar G. Prior Processes and Their Applications: Nonparametric Bayesian Estimation. Springer, 2016.

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33

Lahiri, Parthasarathi. Robust empirical Bayes estimation in finite population sampling. 1986.

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34

Saleh, A. K. Ehsanes. Theory of Preliminary Test and Stein-Type Estimation with Applications. Wiley & Sons, Incorporated, John, 2008.

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35

(Editor), C. R. Smith, and G. Erickson (Editor), eds. Maximum Entropy and Bayesian Spectral Analysis and Estimation Problems (Fundamental Theories of Physics). Springer, 1987.

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36

Tsokos, Chris P., and V. P. Savchuk. Bayesian Statistical Estimation of Reliability Data. World Federation Pub Inc, 2000.

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37

A festschrift for Herman Rubin. Institute of Mathematical Statistics, 2005.

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38

Herman, Rubin, and DasGupta Anirban, eds. A festschrift for Herman Rubin. Institute of Mathematical statistics, 2004.

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39

The signal and the noise: The art and science of prediction. Penguin Books, 2012.

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40

Schorfheide, Frank, and Edward P. Herbst. Bayesian Estimation of DSGE Models. Princeton University Press, 2015.

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41

Bayesian Estimation of DSGE Models. Princeton University Press, 2016.

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42

Harry L. Van Trees (Editor) and Kristine L. Bell (Editor), eds. Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking. Wiley-IEEE Press, 2007.

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43

Constrained Bayesian Methods of Hypotheses Testing: A New Philosophy of Hypotheses Testing in Parallel and Sequential Experiments. Nova Science Pub Inc., 2018.

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44

Françoise, Prêteux, Mohammad-Djafari Ali, Dougherty Edward R, Society of Photo-optical Instrumentation Engineers., and Society for Industrial and Applied Mathematics., eds. Mathematical modeling, Bayesian estimation, and inverse problems: 21-23 July 1999, Denver, Colorado. SPIE, 1999.

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45

Lee, Li-Chu. Empirical Bayes estimation of the response function and multivariate regression model. 1989.

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46

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists (Statistics for Social and Behavioral Sciences). Springer, 2007.

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47

Theory of Preliminary Test and Stein-Type Estimation with Applications (Wiley Series in Probability and Statistics). Wiley-Interscience, 2006.

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48

Chen, Min, J. Michael Dunn, Amos Golan, and Aman Ullah, eds. Advances in Info-Metrics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190636685.001.0001.

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Abstract:
Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In a recent book on the Foundations of Info-Metrics, Golan (OUP, 2018) provides the theoretical underpinning of info-metrics and the necessary tools and building blocks for using that framework. This volume complements Golan’s book and expands on the series of studies on the classical maximum entropy and Bayesian methods published in the different proceedings started with the seminal collection of Levine and Tribus (1979) and continuing annually. The objective of this volume is to expand the study of info-metrics, and information processing, across the sciences and to further explore the basis of information-theoretic inference and its mathematical and philosophical foundations. This volume is inherently interdisciplinary and applications oriented. It contains some of the recent developments in the field, as well as many new cross-disciplinary case studies and examples. The emphasis here is on the interrelationship between information and inference where we view the word ‘inference’ in its most general meaning – capturing all types of problem solving. That includes model building, theory creation, estimation, prediction, and decision making. The volume contains nineteen chapters in seven parts. Although chapters in each part are related, each chapter is self-contained; it provides the necessary tools for using the info-metrics framework for solving the problem confronted in that chapter. This volume is designed to be accessible for researchers, graduate students, and practitioners across the disciplines, requiring only some basic quantitative skills. The multidisciplinary nature and applications provide a hands-on experience for the reader.
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