Bayesian composite Tobit quantile regression

Composite quantile regression models have been shown to be effective techniques in improving the prediction accuracy [H. Zou and M. Yuan, Composite quantile regression and the oracle model selection theory, Ann. Statist. 36 (2008), pp. 1108–1126; J. Bradic, J. Fan, and W. Wang, Penalized composite quasi-likelihood for ultrahighdimensional variable selection, J. R. Stat. Soc. Ser. B 73 (2011), pp. 325–349; Z. Zhao and Z. Xiao, Efficient regressions via optimally combining quantile information, Econometric Theory 30(06) (2014), pp. 1272–1314]. This paper studies composite Tobit quantile regression (TQReg) from a Bayesian perspective. A simple and efficient MCMC-based computation method is derived for posterior inference using a mixture of an exponential and a scaled normal distribution of the skewed Laplace distribution. The approach is illustrated via simulation studies and a real data set. Results show that combine information across different quantiles can provide a useful method in efficient statistical estimation. This is the first work to discuss composite TQReg from a Bayesian perspective.     

Ethnographies of Volunteering: Providing Nuance to the Links Between Volunteering and Development

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper explores how ethnographic approaches to third sector and nonprofit studies allow for context-based...     

An optimization approach applied to the optimal stratification problem

A new optimization algorithm is presented to solve the stratification problem. Assuming the number L of strata and the total sample size n are fixed, we obtain strata boundaries by using an objective function associated with the variance. In this problem, strata boundaries must be determined so that the elements in each stratum are more homogeneous among themselves. To produce more homogeneous strata, this paper proposes a new algorithm that uses the Greedy Randomized Adaptive Search Procedure (GRASP) methodology. Computational results are presented for a set of problems, with the application of the new algorithm and some algorithms from literature.     

Comparison: Israeli Families Anxiety from SCUD Missiles Versus Palestinian Families Anxiety Since the Intifada

This is a study of 309 Palestinian families comparing their current trauma with the trauma experienced by Israeli families during the Gulf War during the SCUD missile attacks. Both populations have experienced adaptations of trauma but the Palestinian fathers have generally been more effected than their counterpart Israeli fathers. There are less reported symptoms of trauma when the victims have an active role to resist trauma.     

Contextual movement models based on normalizing flows

AStA Advances in Statistical Analysis - Movement models predict positions of players (or objects in general) over time and are thus key to analyzing spatiotemporal data as it is often used in...     

Volunteering Hierarchies in the Global South: Remuneration and Livelihoods

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper explores volunteering and inequality in the global South through an analysis of volunteering remuneration. We...     

Comparison: Israeli families anxiety from SCUD missiles versus Palestinian families anxiety since the Intifada

This is a study of 309 Palestinian families comparing their current trauma with the trauma experienced by Israeli families during the Gulf War during the SCUD missile attacks. Both populations have experienced adaptations of trauma but the Palestinian fathers have generally been more effected than their counterpart Israeli fathers. There are less reported symptoms of trauma when the victims have an active role to resist trauma.