This paper builds on recent research that focuses on regression modeling of continuous bounded data, such as proportions measured on a continuous scale. Specifically, it deals with beta regression models with mixed effects from a Bayesian approach. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter, and allow both parameters to be modeled through r...

The inflated beta regression model aims to enable the modeling of responses in the intervals (0,1], [0,1) or [0,1]. In this model, hypothesis testing is often performed based on the likelihood ratio statistic. The critical values are obtained from asymptotic approximations, which may lead to distortions of size in small samples. In this sense, this paper proposes the bootstrap Bartlett correcti...

We introduce c-lasso, a Python package that enables sparse and robust linear regression classification with equality constraints. The underlying statistical forward model is assumed to be of the following form: \[ y = X \beta + \sigma \epsilon \qquad \textrm{subject to} C\beta=0 \] Here, $X \in \mathbb{R}^{n\times d}$is given design matrix vector $y \mathbb{R}^{n}$ continuous or binary response...

when research on repatriation has shown that repatriates quit within one year of return from a foreign assignment, this study attempts to find what makes some repatriates stay committed and loyal to their companies when their colleagues are quitting and joining their immediate competitors? the research further extends to explore - factors determining repatriates loyalty, repatriates’ most desir...

the need for more comparisons among models is widely recognized. this study aimed to compare three different modelling approaches for their capability to simulate and predict trends and patterns of winter wheat yield in western germany. the three modelling approaches included an empirical model, a process-based model (lintul2), and a metamodel derived from the process-based model. the models ou...

background: existence or non-existence of adverse selection in insurance market is one of the important cases that have always been considered by insurers. adverse selection is one of the consequences of asymmetric information. theory of adverse selection states that high-risk individuals demand the insurance service more than low risk individuals do. methods: the presence of adverse selection ...