The deviance information criterion (DIC) introduced by Spiegelhalter et al. (2002) for model assessment and model comparison is directly inspired by linear and generalised linear models, but it is open to different possible variations in the setting of missing data models, depending in particular on whether or not the missing variables are treated as parameters. In this paper, we reassess the c...

The BEKK model is a popular multivariate GARCH processes. The paper develops a new general asymmetric BEKK structure, which is based on recent empirical findings by semi-parametric news impact curves. For estimating the new model, a Markov chain Monte Carlo technique is used. Empirical results for triviarte asset returns from firms in the US indicate that the deviance information criterion favo...

BACKGROUND Musculoskeletal disorders (MSDs) are a common problem among carpet weavers. This study was undertaken to introduce affecting personal and occupational factors in developing the number of MSDs among carpet weavers. METHODS A cross-sectional study was performed among 862 weavers in seven towns with regard to workhouse location in urban or rural regions. Data were collected by using q...

We consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly deened. We follow Dempster in examining the posterior distribution of the log-likelihood under each model, from which we derive measures of t and complexity (the eeective number of parameters). These may be combined into a Deviance Information Criterion (DIC), which is shown to have...

We consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly de ned We follow Dempster in examining the posterior distribution of the log likelihood under each model from which we derive measures of t and complexity the e ective number of parameters These may be combined into a Deviance Information Criterion DIC which is shown to have an appr...

Copula functions and marginal distributions are combined to produce multivariate distributions. We show advantages of estimating all parameters of these models using the Bayesian approach, which can be done with standard Markov chain Monte Carlo algorithms. Deviance-based model selection criteria are also discussed when applied to copula models since they are invariant under monotone increasing...

An R package mixAK is introduced which implements routines for a semiparametric density estimation through normal mixtures using the Markov chain Monte Carlo (MCMC) methodology. Besides producing the MCMC output, the package computes posterior summary statistics for important characteristics of the fitted distribution or computes and visualizes the posterior predictive density. For the estimate...

It is widely established that the Big Five personality traits of conscientiousness, agreeableness, and emotional stability are antecedents to workplace deviance (Berry, Ones, & Sackett, 2007). However, these meta-analytic findings are based on self-reported personality traits. A recent meta-analysis by Oh, Wang, and Mount (2011) identified the value of acquaintance-reported personality in the p...

In regular statistical models, the leave-one-out cross-validation is asymptotically equivalent to the Akaike information criterion. However, since many learning machines are singular statistical models, the asymptotic behavior of the cross-validation remains unknown. In previous studies, we established the singular learning theory and proposed a widely applicable information criterion, the expe...

Many diagnostic tools and goodness-of-fit measures, such as the Akaike information criterion (AIC) and the Bayesian deviance information criterion (DIC), are available to evaluate the overall adequacy of linear regression models. In addition, visually assessing adequacy in models has become an essential part of any regression analysis. In this paper, we focus on a spatial consideration of the l...