1: In this paper we discuss measures of information and divergence and model selection criteria. Three classes of measures, Fisher-type, divergencetype and entropy-type measures, are discussed and their properties are presented. Information through censoring and truncation is presented and model selection criteria are investigated including the Akaike Information Criterion (AIC) and the Diverge...

We consider parameter estimation, hypothesis testing and variable selection for partially time-varying coefficient models. Our asymptotic theory has the useful feature that it can allow dependent, nonstationary error and covariate processes. With a two-stage method, the parametric component can be estimated with a n-convergence rate. A simulation-assisted hypothesis testing procedure is propose...

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Panel datasets have been increasingly used in economics to analyse complex economic phenomena. One of the attractions of panel datasets is the ability to use an extended dataset to obtain information about parameters of interest which are assumed to have common values across panel units. However, the assumption of poolability has not been studied extensively beyond tests that determine whether ...

We consider the quality of learning a response function by a nonparametric Bayesian approach using a Gaussian process (GP) prior on the response function. We upper bound the quadratic risk of the learning procedure, which in turn is an upper bound on the Kullback-Leibler information between the predictive and true data distribution. The upper bound is expressed in small ball probabilities and c...

This study was conducted to estimate the genetic parameters of litter size (LS) in Moghani sheep using threshold model via Bayesian approach. The data originated from the Jafar-Abad Station of Ardabil province, Iran, and included 9698 lactation records of 4977 ewes with lambings from 1995 until 2010. The pedigree file consisted of data on animals born from 1987 to 2010. The significance of fixe...

A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization a...

Reinforcement learning (RL) methods based on direct policy search (DPS) have been actively discussed to achieve an efficient approach to complicated Markov decision processes (MDPs). Although they have brought much progress in practical applications of RL, there still remains an unsolved problem in DPS related to model selection for the policy. In this paper, we propose a novel DPS method, weig...

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000–2007. With the census tract level as ...

In failure time distributions, inliers in a data set are subset of observations sufficiently small relative to the rest of the observations, which appears to be inconsistent with the remaining data set. They are either the resultant of instantaneous failures or early failures, experienced in many life-testing experiments. The model used in outliers, where r observations are outliers is modified...