Bayesian Nonparametric Hidden Markov Models with application to the analysis of copy-number-variation in mammalian genomes

We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models. Our approach uses a Mixture of Dirichlet Process (MDP) model for the unknown sampling distribution (likelihood) for the observations arising in each state and a computationally efficient data augmentation scheme to aid inference. The method uses novel MCMC methodology which combines recent retrospective sampling methods with the use of slice sampler variables. The methodology is computationally efficient, both in terms of MCMC mixing properties, and robustness to the length of the time series being investigated. Moreover, the method is easy to implement requiring little or no user-interaction. We apply our methodology to the analysis of genomic copy number variation.     

Epsilon Birnbaum–Saunders distribution family: properties and inference

In this paper we introduce a new extension for the Birnbaum–Saunder distribution based on the family of the epsilon-skew-symmetric distributions studied in Arellano-Valle et al. (J Stat Plan Inference 128(2):427–443, 2005). The extension allows generating Birnbaun–Saunders type distributions able to deal with extreme or outlying observations (Dupuis and Mills, IEEE Trans Reliab 47:88–95, 1998). Basic properties such as moments and Fisher information matrix are also studied. Results of a real data application are reported illustrating good fitting properties of the proposed model.     

Estimating variation from data with varying element sizes

In some applications (repeated surveys, process control, monitoring use of resources etc), observations are often based on elements of varying size. This paper describes two methods of estimating the underlying variation. One method measures deviations from an overall estimate of a location parameter, while the other method is based on successive differences. Both are 'one-pass' estimates and are thus programmable without storing all the data.     

Four tests of fit for the beta-binomial distribution

Tests based on the Anderson–Darling statistic, a third moment statistic and the classical Pearson–Fisher X ² statistic, along with its third-order component, are considered. A small critical value and power study are given. Some examples illustrate important applications.     

MORE INFORMATIVE TESTING FOR BIVARIATE SYMMETRY

In testing for bivariate symmetry against arbitrary alternatives the well‐known test developed by Bowker in 1948 is shown to be a score test, and to have useful components. These components are asymptotically independent and asymptotically have the standard normal distribution. Moreover they assess particular pairs of cells for symmetry. These components can also be used in a data analytic manner to complement a test for bivariate symmetry against ordered alternatives.     

A further examination of antecedents of correctional staff life satisfaction

Working in corrections is not only a demanding job, but a socially important one. While a growing number of studies have examined how the work environment impacts the job stress, job satisfaction, and organizational commitment of staff, very few studies have examined how working in corrections impacts the life satisfaction of workers. The current study utilized OLS regression to examine the antecedents of life satisfaction among staff at a Midwestern private prison. Job satisfaction had a positive relationship with life satisfaction, while age, work on family conflict, family on work conflict, and job involvement all had statistically significant negative effects. Finally, perceptions of the level of financial rewards, job stress, organizational commitment, gender, race, educational level, tenure, supervisory status, position, marital status, and having children, all had non-significant associations with overall satisfaction with life.     

Subjective Versus Objective Definitions of Homelessness: Are there Differences in Risk Factors among Heavy-Drinking Women?

Investigations with homeless populations have focused on those living on the streets or in shelters; few have examined phenomena based on respondents’ self-definitions as homeless or not. This investigation examined similarities and differences among risk factors (including mental health, substance abuse, religion/spirituality, social support, and risky sexual behaviors) using two definitions of homelessness: one where place of residence defined individuals as homeless (the ‘objective’ or traditional, definition) and another where respondents defined themselves as homeless (the ‘subjective’ definition). Data come from the baseline survey of the NIAAA-funded “Sister-to-Sister” study (n = 339) of heavy-drinking women. Subjectively defined homelessness was associated with higher rates of mental health and substance use disorders, lower rates of condom use, higher rates of trading sex for food, and less social support. Objectively defined homelessness was associated with higher rates of drinking in abandoned buildings, on the streets, and in public restrooms, more new sexual partners, and higher rates of trading sex for heroin and speedballs. Investigations failing to ask for subjective information may misattribute some factors to homelessness which may overestimate the effect of various factors on homelessness. Investigators should ask respondents to define their homelessness, or they lose an important dimension of the concept of homelessness.