Results 21  30
of
136,492
Empirical Bayes Estimation for the Stochastic Blockmodel
, 2014
"... Inference for the stochastic blockmodel is currently of burgeoning interest in the statistical community, as well as in various application domains as diverse as social networks, citation networks, brain connectivity networks (connectomics), etc. Recent theoretical developments have shown that spect ..."
Abstract
 Add to MetaCart
that spectral embedding of graphs yields tractable distributional results; in particular, a random dot product latent position graph formulation of the stochastic blockmodel informs a mixture of normal distributions for the adjacency spectral embedding. We employ this new theory to provide an empirical Bayes
Empirical Bayes Inference in Structured Hazard Regression 3
"... • Leukemia survival data. • Structured hazard regression for continuous survival times. • Empirical Bayes inference in structured hazard regression. • Multistate models. ..."
Abstract
 Add to MetaCart
• Leukemia survival data. • Structured hazard regression for continuous survival times. • Empirical Bayes inference in structured hazard regression. • Multistate models.
Bayes Factors
, 1995
"... In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null ..."
Abstract

Cited by 1766 (74 self)
 Add to MetaCart
In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null
Microarrays, empirical Bayes and the twogroups model
 STATIST. SCI
, 2006
"... The classic frequentist theory of hypothesis testing developed by Neyman, Pearson, and Fisher has a claim to being the Twentieth Century’s most influential piece of applied mathematics. Something new is happening in the TwentyFirst Century: high throughput devices, such as microarrays, routinely re ..."
Abstract

Cited by 73 (10 self)
 Add to MetaCart
require simultaneous hypothesis tests for thousands of individual cases, not at all what the classical theory had in mind. In these situations empirical Bayes information begins to force itself upon frequentists and Bayesians alike. The twogroups model is a simple Bayesian construction that facilitates
Bayes and empirical Bayes changepoint problems
, 2009
"... We generalize the approach of Liu and Lawrence (1999) for multiple changepoint problems where the number of changepoints is unknown. The approach is based on dynamic programming recursion for efficient calculation of the marginal probability of the data with the hidden parameters integrated out. For ..."
Abstract
 Add to MetaCart
We generalize the approach of Liu and Lawrence (1999) for multiple changepoint problems where the number of changepoints is unknown. The approach is based on dynamic programming recursion for efficient calculation of the marginal probability of the data with the hidden parameters integrated out. For the estimation of the hyperparameters, we propose to use Monte Carlo EM when training data are available. We argue that there is some advantages of using samples from the posterior which takes into account the uncertainty of the changepoints, compared to the traditional MAP estimator, which is also more expensive to compute in this context. The samples from the posterior obtained by our algorithm are independent, getting rid of the convergence issue associated with the MCMC approach. We illustrate our approach on limited simulations and some real data set.
EMPIRICAL BAYES ESTIMATION OF FINITE POPULATION VARIANCES
"... SUMMARY. The KleffeRao model, a mixed model with random sampling variances, is extended to produce empirical Bayes estimators of several finite population variances. The proposed empirical Bayes estimators do not have a closed form. A second order Laplace approximation is used which works well for ..."
Abstract
 Add to MetaCart
SUMMARY. The KleffeRao model, a mixed model with random sampling variances, is extended to produce empirical Bayes estimators of several finite population variances. The proposed empirical Bayes estimators do not have a closed form. A second order Laplace approximation is used which works well
Bayes and Empirical Bayes Estimation for the Chain Ladder Model
 ASTIN Bulletin
, 1990
"... The 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 whic ..."
Abstract

Cited by 17 (0 self)
 Add to MetaCart
approach to the chain ladder technique can be derived. The Bayesian results allow the input of collateral information i 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
An assessment of empirical Bayes and composite estimators for small areas
"... We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the arealevel means can be inefficient. ..."
Abstract
 Add to MetaCart
We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the arealevel means can be inefficient.
An Empirical Bayes Approach to Estimating Loss Ratios
"... The empirical Bayes model is explored as a technique for estimating key financial variables that are meaningful to regulators, policyholders, and security analysts of propertyliability insurers. The time series mean and two empirical Bayes models of the loss ratio are evaluated for four lines of bu ..."
Abstract
 Add to MetaCart
The empirical Bayes model is explored as a technique for estimating key financial variables that are meaningful to regulators, policyholders, and security analysts of propertyliability insurers. The time series mean and two empirical Bayes models of the loss ratio are evaluated for four lines
Results 21  30
of
136,492