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Journal articles on the topic 'Empirical Bayes methods'

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Published: 4 June 2021

Last updated: 21 February 2023

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1

Lindley, D. V., J. S. Maritz, and T. Lwin. "Empirical Bayes Methods." Mathematical Gazette 74, no. 467 (March 1990): 91. http://dx.doi.org/10.2307/3618894.

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2

Bagghi, Parthasarathy, J. S. Maritz, and T. Lwin. "Empirical Bayes Methods." Journal of the American Statistical Association 86, no. 413 (March 1991): 244. http://dx.doi.org/10.2307/2289739.

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3

Angus, John E. "Empirical Bayes Methods." Technometrics 33, no. 2 (May 1991): 243–45. http://dx.doi.org/10.1080/00401706.1991.10484821.

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4

Stephenson, W. Robert. "Empirical Bayes Methods." Journal of Quality Technology 22, no. 3 (July 1990): 249–50. http://dx.doi.org/10.1080/00224065.1990.11979250.

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5

Young, Karen, J. Maritz, and T. Lwin. "Empirical Bayes Methods." Applied Statistics 41, no. 3 (1992): 604. http://dx.doi.org/10.2307/2348097.

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6

Denham, Mike, J. S. Maritz, and T. Lwin. "Empirical Bayes Methods." Statistician 39, no. 1 (1990): 97. http://dx.doi.org/10.2307/2348214.

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7

Laird, Nan M., and Thomas A. Louis. "Empirical Bayes Ranking Methods." Journal of Educational Statistics 14, no. 1 (March 1989): 29–46. http://dx.doi.org/10.3102/10769986014001029.

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Ranking problems arise in setting priorities for investigations, in providing a simple summary of performance, in comparing objects in a manner robust to measurement scale, and in a wide variety of other applications. Commonly, rankings are computed from measurements that depend on the true attribute. Using the Gaussian model, we propose and compare methods for using these measurements to estimate the ranks of the underlying attributes and show that those based on an empirical Bayes model produce estimates that differ from ranking observed data. These differences result both from the effect of shrinking posterior means towards a common value by an amount that depends on the precision of individual measurements and from the Bayes processing of the posterior distribution to produce estimates that account for the uncertainty in the distribution of the ranks. We illustrate different ranking methods using data on school achievement reported by Aitkin and Longford (1986) . Mathematical and empirical results highlight the importance of using appropriate ranking methods and identify issues requiring further research.

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8

Laird, Nan M., and Thomas A. Louis. "Empirical Bayes Ranking Methods." Journal of Educational Statistics 14, no. 1 (1989): 29. http://dx.doi.org/10.2307/1164724.

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9

Casella, George. "Illustrating empirical Bayes methods." Chemometrics and Intelligent Laboratory Systems 16, no. 2 (October 1992): 107–25. http://dx.doi.org/10.1016/0169-7439(92)80050-e.

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10

Maritz, J. S., and T. Lwin. "Empirical Bayes Methods, 2nd Edition." Biometrics 46, no. 3 (September 1990): 886. http://dx.doi.org/10.2307/2532124.

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11

Lindley, D. V., Bradley P. Carlin, Thomas A. Louis, Jose M. Bernardo, and Adrian F. M. Smith. "Bayes and Empirical Bayes Methods for Data Analysis." Mathematical Gazette 85, no. 503 (July 2001): 381. http://dx.doi.org/10.2307/3622080.

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12

Leonard, T., B. P. Carlin, and T. A. Louis. "Bayes and Empirical Bayes Methods for Data Analysis." Biometrics 53, no. 1 (March 1997): 385. http://dx.doi.org/10.2307/2533126.

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13

Jones, David R. "Bayes and Empirical Bayes methods for date analysis." International Journal of Epidemiology 30, no. 4 (August 2001): 910. http://dx.doi.org/10.1093/ije/30.4.910.

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14

Rukhin, Andrew L. "Bayes and Empirical Bayes Methods for Data Analysis." Technometrics 39, no. 3 (August 1997): 337. http://dx.doi.org/10.1080/00401706.1997.10485131.

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15

Leyland, Alastair H., and Carolyn A. Davies. "Empirical Bayes methods for disease mapping." Statistical Methods in Medical Research 14, no. 1 (February 2005): 17–34. http://dx.doi.org/10.1191/0962280205sm387oa.

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16

Martinsek, Adam T. "Empirical bayes methods in sequential estimation." Sequential Analysis 6, no. 2 (January 1987): 119–37. http://dx.doi.org/10.1080/07474948708836120.

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17

Greis, Noel P., and C. Zachary Gilstein. "Empirical Bayes methods for telecommunications forecasting." International Journal of Forecasting 7, no. 2 (August 1991): 183–97. http://dx.doi.org/10.1016/0169-2070(91)90053-x.

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18

Efron, Bradley. "Empirical Bayes Methods for Combining Likelihoods." Journal of the American Statistical Association 91, no. 434 (June 1996): 538–50. http://dx.doi.org/10.1080/01621459.1996.10476919.

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19

Bar, Haim, and Kangyan Liu. "Empirical Bayes methods in variable selection." Wiley Interdisciplinary Reviews: Computational Statistics 11, no. 2 (October 17, 2018): e1455. http://dx.doi.org/10.1002/wics.1455.

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20

Gu, Jiaying, and Roger Koenker. "Empirical Bayesball Remixed: Empirical Bayes Methods for Longitudinal Data." Journal of Applied Econometrics 32, no. 3 (June 20, 2016): 575–99. http://dx.doi.org/10.1002/jae.2530.

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21

Stangl, Dalene. "Book Review: Bayes and empirical Bayes methods for data analysis." Statistical Methods in Medical Research 7, no. 2 (April 1998): 205. http://dx.doi.org/10.1177/096228029800700207.

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22

Stangl, Dalene. "Book Review: Bayes and empirical Bayes methods for data analysis." Statistical Methods in Medical Research 8, no. 4 (August 1999): 335. http://dx.doi.org/10.1177/096228029900800410.

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23

Ver Hoef, Jay M. "Parametric Empirical Bayes Methods for Ecological Applications." Ecological Applications 6, no. 4 (November 1996): 1047–55. http://dx.doi.org/10.2307/2269589.

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24

Gelfand, Alan E. "Empirical Bayes Methods for Combining Likelihoods: Comment." Journal of the American Statistical Association 91, no. 434 (June 1996): 551. http://dx.doi.org/10.2307/2291647.

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25

George, Edward I. "Empirical Bayes Methods for Combining Likelihoods: Comment." Journal of the American Statistical Association 91, no. 434 (June 1996): 553. http://dx.doi.org/10.2307/2291648.

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26

Morris, Carl N. "Empirical Bayes Methods for Combining Likelihoods: Comment." Journal of the American Statistical Association 91, no. 434 (June 1996): 555. http://dx.doi.org/10.2307/2291649.

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27

Reid, N. "Empirical Bayes Methods for Combining Likelihoods: Comment." Journal of the American Statistical Association 91, no. 434 (June 1996): 559. http://dx.doi.org/10.2307/2291650.

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28

Severini, Thomas A., and Martin A. Tanner. "Empirical Bayes Methods for Combining Likelihoods: Comment." Journal of the American Statistical Association 91, no. 434 (June 1996): 560. http://dx.doi.org/10.2307/2291651.

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29

Efron, Bradley. "Empirical Bayes Methods for Combining Likelihoods: Rejoinder." Journal of the American Statistical Association 91, no. 434 (June 1996): 562. http://dx.doi.org/10.2307/2291652.

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30

Koopman, S. J., and G. Mesters. "Empirical Bayes Methods for Dynamic Factor Models." Review of Economics and Statistics 99, no. 3 (July 2017): 486–98. http://dx.doi.org/10.1162/rest_a_00614.

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31

Louis, Thomas A. "Using empirical bayes methods in biopharmaceutical research." Statistics in Medicine 10, no. 6 (June 1991): 811–29. http://dx.doi.org/10.1002/sim.4780100604.

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32

Louis, Thomas A., and Wei Shen. "Innovations in Bayes and empirical Bayes methods: estimating parameters, populations and ranks." Statistics in Medicine 18, no. 17-18 (September 15, 1999): 2493–505. http://dx.doi.org/10.1002/(sici)1097-0258(19990915/30)18:17/18<2493::aid-sim271>3.0.co;2-s.

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33

Sugasawa, Shonosuke, Tatsuya Kubokawa, and Kota Ogasawara. "Empirical Uncertain Bayes Methods in Area-level Models." Scandinavian Journal of Statistics 44, no. 3 (April 4, 2017): 684–706. http://dx.doi.org/10.1111/sjos.12271.

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34

Butcher, Jonathan B., Miguel A. Medina, and Carlos M. Marin. "Empirical Bayes regionalization methods for spatial stochastic processes." Water Resources Research 27, no. 1 (January 1991): 7–15. http://dx.doi.org/10.1029/90wr01879.

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35

Abdoli, Mansour, and F. Fred Choobineh. "Empirical Bayes forecasting methods for job flow times." IIE Transactions 37, no. 7 (July 2005): 635–49. http://dx.doi.org/10.1080/07408170590948495.

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36

Petrone, Sonia, Stefano Rizzelli, Judith Rousseau, and Catia Scricciolo. "Empirical Bayes methods in classical and Bayesian inference." METRON 72, no. 2 (June 3, 2014): 201–15. http://dx.doi.org/10.1007/s40300-014-0044-1.

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37

Braun, Henry I. "EMPIRICAL BAYES METHODS: A TOOL FOR EXPLORATORY ANALYSIS." ETS Research Report Series 1988, no. 1 (June 1988): i—55. http://dx.doi.org/10.1002/j.2330-8516.1988.tb00281.x.

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38

Stijnen, Th, and J. C. Van Houwelingen. "Empirical Bayes Methods in Clinical Trials Meta-Analysis." Biometrical Journal 32, no. 3 (January 18, 2007): 335–46. http://dx.doi.org/10.1002/bimj.4710320316.

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39

Yanuar, Ferra, Rahmatika Fajriyah, and Dodi Devianto. "SMALL AREA ESTIMATION METHOD WITH EMPIRICAL BAYES BASED ON BETA BINOMIAL MODEL IN GENERATED DATA." MEDIA STATISTIKA 14, no. 1 (October 21, 2020): 1–9. http://dx.doi.org/10.14710/medstat.14.1.1-9.

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Small Area Estimation is one of the methods that can be used to estimate parameters in an area that has a small population. This study aims to estimate the value of the binary data parameter using the direct estimation method and an indirect estimation method by using the Empirical Bayes approach. To illustrate the method, we consider three conditions: direct estimator, empirical Bayes (EB) with auxiliary variables, and empirical Bayes without auxiliary variables. The smaller value of Mean Square Error is used to determine the better method. The results showed that the indirect estimation methods (EB method) gave the parameter value that was not much different from the direct estimation value. Then, the MSE values of indirect estimation with an auxiliary variable are smaller than the direct estimation method.

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40

Devine, Owen J., Thomas A. Louis, and M. Elizabeth Halloran. "Empirical Bayes Methods for Stabilizing Incidence Rates before Mapping." Epidemiology 5, no. 6 (November 1994): 622–30. http://dx.doi.org/10.1097/00001648-199411000-00010.

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41

Zhang, Cun-Hui. "Compound decision theory and empirical Bayes methods: invited paper." Annals of Statistics 31, no. 2 (April 2003): 379–90. http://dx.doi.org/10.1214/aos/1051027872.

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42

Samaniego, Francisco J., and Eric Vestrup. "On improving standard estimators via linear empirical Bayes methods." Statistics & Probability Letters 44, no. 3 (September 1999): 309–18. http://dx.doi.org/10.1016/s0167-7152(99)00022-x.

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43

Thomas, Neal, Nicholas T. Longford, and John E. Rolph. "Empirical Bayes methods for estimating hospital-specific mortality rates." Statistics in Medicine 13, no. 9 (May 15, 1994): 889–903. http://dx.doi.org/10.1002/sim.4780130902.

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44

Efron, Bradley, and Robert Tibshirani. "Empirical bayes methods and false discovery rates for microarrays." Genetic Epidemiology 23, no. 1 (June 2002): 70–86. http://dx.doi.org/10.1002/gepi.1124.

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45

Verrall, R. J. "Bayes and Empirical Bayes Estimation for the Chain Ladder Model." ASTIN Bulletin 20, no. 2 (November 1990): 217–43. http://dx.doi.org/10.2143/ast.20.2.2005444.

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AbstractThe subject of predicting outstanding claims on a porfolio of general insurance policies is approached via the theory of hierarchical Bayesian linear models. This is particularly appropriate since the chain ladder technique can be expressed in the form of a linear model. The statistical methods which are applied allow the practitioner to use different modelling assumptions from those implied by a classical formulation, and to arrive at forecasts which have a greater degree of inherent stability. The results can also be used for other linear models. By using a statistical structure, a sound approach to the chain ladder technique can be derived. The Bayesian results allow the input of collateral information in a formal manner. Empirical Bayes results are derived which can be interpreted as credibility estimates. The statistical assumptions which are made in the modelling procedure are clearly set out and can be tested by the practitioner. The results based on the statistical theory form one part of the reserving procedure, and should be followed by expert interpretation and analysis. An illustration of the use of Bayesian and empirical Bayes estimation methods is given.

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46

Heisterkamp, S. H., G. Doornbos, and M. Gankema. "Disease mapping using empirical bayes and bayes methods on mortality statistics in the Netherlands." Statistics in Medicine 12, no. 19-20 (October 1993): 1895–913. http://dx.doi.org/10.1002/sim.4780121915.

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47

Hook, Ernest B. "SIMPLER COMMON-SENSE METHODS MAY BE PREFERABLE TO “EMPIRICAL BAYES”." Epidemiology 6, no. 3 (May 1995): 337. http://dx.doi.org/10.1097/00001648-199505000-00031.

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48

Zhang, Cun-Hui. "General empirical Bayes wavelet methods and exactly adaptive minimax estimation." Annals of Statistics 33, no. 1 (February 2005): 54–100. http://dx.doi.org/10.1214/009053604000000995.

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49

Gianola, D., J. L. Foulley, R. L. Fernando, C. R. Henderson, and K. A. Weigel. "Estimation of Heterogeneous Variances Using Empirical Bayes Methods: Theoretical Considerations." Journal of Dairy Science 75, no. 10 (October 1992): 2805–23. http://dx.doi.org/10.3168/jds.s0022-0302(92)78044-8.

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50

Buta, Eugenia, and Hani Doss. "Computational approaches for empirical Bayes methods and Bayesian sensitivity analysis." Annals of Statistics 39, no. 5 (October 2011): 2658–85. http://dx.doi.org/10.1214/11-aos913.

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