Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Public intellectuals,political satire and the birth of activist public relations: The case of Attic Comedy

The purpose of this article is to explore the origins of dissent public relations and to establish its emergence in the context of the ancient Greek comedy represented by Aristophanes. Indeed, Attic Comedy (also known as Old Comedy) was the first great example of today’s mass communication, in which political satire was used to dissent and protest against political and social circumstances in fifth-century BC Athens. This situation was conditioned by the Peloponnesian War and its political, economic and social consequences. From this perspective, this article also constitutes an investigation into the intellectual history of public relations, of which Aristophanes can be considered to be one of the first practitioners.     

Coordinate sampler: a non-reversible Gibbs-like MCMC sampler

We derive a novel non-reversible, continuous-time Markov chain Monte Carlo sampler, called Coordinate Sampler, based on a piecewise deterministic Markov process, which is a variant of the Zigzag sampler of Bierkens et al. (Ann Stat 47(3):1288–1320, 2019). In addition to providing a theoretical validation for this new simulation algorithm, we show that the Markov chain it induces exhibits geometrical ergodicity convergence, for distributions whose tails decay at least as fast as an exponential distribution and at most as fast as a Gaussian distribution. Several numerical examples highlight that our coordinate sampler is more efficient than the Zigzag sampler, in terms of effective sample size.     

Job-Related Well-Being of Immigrants

Social Indicators Research - Considerable literature exists on the acculturation and adaptation of immigrants. For the most part, studies looked at their psychological and social adaptation to the...     

Activity patterns and temporal niche partitioning of dogs and medium-sized wild mammals in urban parks of Xalapa,Mexico

Urban Ecosystems - Free-ranging domestic dogs are the world most common exotic carnivore species that could negatively interact with the native wildlife as predators, competitors, and disease...     

Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Seasonal fractional ARIMA (ARFISMA) model with infinite variance innovations is used in the analysis of seasonal long-memory time series with large fluctuations (heavy-tailed distributions). Two methods, which are the empirical characteristic function (ECF) procedure developed by Knight and Yu [The empirical characteristic function in time series estimation. Econometric Theory. 2002;18:691–721] and the Two-Step method (TSM) are proposed to estimate the parameters of stable ARFISMA model. The ECF method estimates simultaneously all the parameters, while the TSM considers in the first step the Markov Chains Monte Carlo–Whittle approach introduced by Ndongo et al. [Estimation of long-memory parameters for seasonal fractional ARIMA with stable innovations. Stat Methodol. 2010;7:141–151], combined with the maximum likelihood estimation method developed by Alvarez and Olivares [Méthodes d'estimation pour des lois stables avec des applications en finance. Journal de la Société Française de Statistique. 2005;1(4):23–54] in the second step. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques.     

Happily ever after? Intrahousehold bargaining and the distribution of utility within marriage

Using a rich longitudinal data set of married couples from the Korean Labor and Income Panel Study, this article seeks to uncover the intramarital allocation of experienced utility and its drivers. We find both substantial gains from marriage and effects of relative predicted earnings outside of marriage on relative gains from marriage. These findings are consistent with cooperative bargaining models and with models viewing individuals as having a demand for household production services by a spouse, with market forces influencing the price of such services. In addition, we find that men benefit more from marriage than women and that this gender gap is more pronounced for older couples. This is likely to be due to social norms and prescribed gender roles which are more prevalent within the older generation.     

Robust Bayesian nonlinear mixed‐effects modeling of time to positivity in tuberculosis trials

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti‐TB drugs. The EBA of anti‐TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long‐term efficacy of anti‐TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed‐effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed‐effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent “deletion” of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.     

The Interview for Decisional Abilities (IDA): a tool to assess the decisional capacity of abused and neglected older adults

We present the Interview for Decisional Abilities (IDA), a semi-structured tool for use by adult protective services (APS) workers as part of their comprehensive assessments of clients. The IDA was created in response to a Federal mandate to standardize the procedures and competencies of APS agencies with a view to improving client assessments and facilitating cross-jurisdictional research on adult mistreatment. The proximal aim of the IDA is to guide workers in gathering information on the ability of suspected victims of adult mistreatment to make decisions about the risks they face.