Empirical Bayesball Remixed: Empirical Bayes Methods for Longitudinal Data

Gu, Jiaying; Koenker, Roger

doi:10.1002/jae.2530

Cited by 31 publications

(22 citation statements)

References 43 publications

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“…Under certain conditions, the optimal solution from this perspective is closely related to nonparametric empirical Bayes estimators (Brown and Greenshtein, 2009;Jiang et al, 2009;Zhang, 2003 (Castillo et al, 2012;Johnstone, 1994, 1995;Martin et al, 2014). Heteroscedastic normal sequences, where the X i1 can have different variances for different indices i, have also been considered, both when the variances are known (Fu et al, 2019;Tan, 2016;Weinstein et al, 2018;Xie et al, 2012;Zhang and Bhattacharya, 2017) and when they are unknown but estimates are available (Feng and Dicker, 2018;Gu and Koenker, 2017;Jing et al, 2016).…”

Section: Previous Workmentioning

confidence: 99%

Simultaneous estimation of normal means with side information

Zhao¹

2021

STAT SINICA

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The integrative analysis of multiple datasets is an important strategy in data analysis. It is increasingly popular in genomics, which enjoys a wealth of publicly available datasets that can be compared, contrasted, and combined in order to extract novel scientific insights. This paper studies a stylized example of data integration for a classical statistical problem: leveraging side information to estimate a vector of normal means. This task is formulated as a compound decision problem, an oracle integrative decision rule is derived, and a data-driven estimate of this rule based on minimizing an unbiased estimate of its risk is proposed. The data-driven rule is shown to asymptotically achieve the minimum possible risk among all separable decision rules, and it can outperform existing methods in numerical properties. The proposed procedure leads naturally to an integrative high-dimensional classification procedure, which is illustrated by combining data from two independent gene expression profiling studies.

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Section: Previous Workmentioning

confidence: 99%

Simultaneous estimation of normal means with side information

Zhao¹

2021

STAT SINICA

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“…The data come from a survey designed to elicit WTP estimates for elite sporting success in the Olympic Games. Sports represent an interesting setting for comparing different econometric methods (Gu and Koenker, 2017). National, state and local governments heavily subsidize the sports industry.…”

Section: Contextmentioning

confidence: 99%

Validity and reliability of contingent valuation and life satisfaction measures of welfare: An application to the value of national Olympic success

Humphreys

Johnson

Whitehead

2020

Southern Economic Journal

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The contingent valuation method (CV) has long been used to estimate nonmarket values of environmental and other public goods and amenities. Recently, life satisfaction (LS) measures have been used to estimate nonmarket values. This paper empirically compares CV and LS measures of welfare. We elicit willingness-to-pay (WTP) estimates for medals won by Canadian athletes and LS measures using Canadian survey data collected before and after the 2010 Winter Olympic Games. These data permit comparative analyses of reliability and validity of CV and LS measures. Both exhibit econometric reliability. CV and LS WTP estimates for medals increases after the Olympics. CV measures of WTP exhibit temporal reliability but LS measures of welfare lack temporal reliability and are significantly greater than CV measures.

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“…An implementation is available in the function WTLVmix of REBayes. Gu and Koenker (2015a) describe an application to predicting baseball batting averages in which following Brown (2008) averages are transformed to normality, and the θ's reflect either under or over dispersion relative to the standard binomial model. Again, profile likelihood is used to explore covariate effects embedded in this model of heterogeneity.…”

Section: Gaussian Mixture Modelsmentioning

confidence: 99%

Rebayes: an R package for empirical bayes mixture methods

Gu¹,

Koenker²

2017

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Models of unobserved heterogeneity, or frailty as it is commonly known in survival analysis, can often be formulated as semiparametric mixture models and estimated by maximum likelihood as proposed by Robbins (1950) and elaborated by Kiefer and Wolfowitz (1956). Recent developments in convex optimization, as noted by Koenker and Mizera (2014b), have led to dramatic improvements in computational methods for such models. In this vignette we describe an implementation contained in the R package REBayes with applications to a wide variety of mixture settings: Gaussian location and scale, Poisson and binomial mixtures for discrete data, Weibull and Gompertz models for survival data, and several Gaussian models intended for longitudinal data. While the dimension of the nonparametric heterogeneity of these models is inherently limited by our present gridding strategy, we describe how additional fixed parameters can be relatively easily accommodated via profile likelihood. We also describe some nonparametric maximum likelihood methods for shape and norm constrained density estimation that employ related computational methods.

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Empirical Bayesball Remixed: Empirical Bayes Methods for Longitudinal Data

Cited by 31 publications

References 43 publications

Simultaneous estimation of normal means with side information

Simultaneous estimation of normal means with side information

Validity and reliability of contingent valuation and life satisfaction measures of welfare: An application to the value of national Olympic success

Rebayes: an R package for empirical bayes mixture methods

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