The competing risks analysis for parallel and series systems using Type-II progressive censoring

Abstract

Recently, the study of the lifetime of systems in reliability and survival analysis in the presence of several causes of failure (competing risks) has attracted attention in the literature. In this paper, series and parallel systems with exponential lifetime for each item of the system are considered. Several causes of failure independently affect lifetime distributions and observations of failure times of the systems are considered under progressive Type-II censored scheme. For series systems, the maximum likelihood estimates of parameters are computed and confidence intervals for parameters of the model are obtained using Fisher information matrix. For parallel systems, the generalized EM algorithm which uses the Newton-Raphson algorithm inside the EM algorithm is used to compute the maximum likelihood estimates of parameters. Also, the standard errors of the maximum likelihood estimates are computed by using the supplemented EM algorithm. The simulation study confirms the good performance of the introduced approach.     

On the Estimation of the Density of a Directional Data Stream

Many directional data such as wind directions can be collected extremely easily so that experiments typically yield a huge number of data points that are sequentially collected. To deal with such big data, the traditional nonparametric techniques rapidly require a lot of time to be computed and therefore become useless in practice if real time or online forecasts are expected. In this paper, we propose a recursive kernel density estimator for directional data which (i) can be updated extremely easily when a new set of observations is available and (ii) keeps asymptotically the nice features of the traditional kernel density estimator. Our methodology is based on Robbins–Monro stochastic approximations ideas. We show that our estimator outperforms the traditional techniques in terms of computational time while being extremely competitive in terms of efficiency with respect to its competitors in the sequential context considered here. We obtain expressions for its asymptotic bias and variance together with an almost sure convergence rate and an asymptotic normality result. Our technique is illustrated on a wind dataset collected in Spain. A Monte‐Carlo study confirms the nice properties of our recursive estimator with respect to its non‐recursive counterpart.     

Some multivariate singular unified skew-normal distributions and their application

Abstract

We introduce here the truncated version of the unified skew-normal (SUN) distributions. By considering a special truncations for both univariate and multivariate cases, we derive the joint distribution of consecutive order statistics X_{(r, ..., r + k)} = (X_(r), ..., X_{(r + K)})^T from an exchangeable n-dimensional normal random vector X. Further we show that the conditional distributions of X_{(r + j, ..., r + k)} given X_{(r, ..., r + j ? 1)}, X_{(r, ..., r + k)} given (X_(r) > t)?and X_{(r, ..., r + k)} given (X_{(r + k)} < t) are special types of singular SUN distributions. We use these results to determine some measures in the reliability theory such as the mean past life (MPL) function and mean residual life (MRL) function.     

Consistency of the recursive nonparametric regression estimation for dependent functional data

We consider the recursive estimation of a regression functional where the explanatory variables take values in some functional space. We prove the almost sure convergence of such estimates for dependent functional data. Also we derive the mean quadratic error of the considered class of estimators. Our results are established with rates and asymptotic appear bounds, under strong mixing condition. Finally, the feasibility of the proposed estimator is illustrated throughout an empirical study.     

Effort-reward imbalance and work-home interference: a two-wave study among European male nurses

ABSTRACT

This one-year follow-up study among 1,421 male nurses from seven European countries tested the validity of the Effort-Reward Imbalance (ERI) model in predicting prospective vital exhaustion and work-home interference. We hypothesised that effort and lack of reward would have both main and interactive effects on future outcomes. Results of structural equation modelling (SEM) showed that effort was positively related to exhaustion and work-home interference, both simultaneously and over time. Lack of reward predicted increased exhaustion at follow-up, but effort-reward imbalance did not influence the outcomes. Additionally, Time 1 exhaustion predicted increased work-home interference and exhaustion at follow-up. These results do not support the ERI model, which postulates a primacy of effort-reward imbalance over main effects. Instead, the findings are in line with dual path models of job stress and work-home interference. Multi-group SEM showed partial cross-cultural metric invariance for the ERI measure of effort, but the ERI measure of rewards showed no metric measurement invariance, indicating its meaning is qualitatively different across cultures. Nevertheless, the main conclusions were markedly similar for each national sub-sample. We discuss the theoretical and practical implications of our study.     

Exploring teachers’ career self-management. Considering the roles of organizational career management,occupational self-efficacy,and learning goal orientation.

The current study examines how organizational career management – i.e. activities undertaken by schools in order to plan and manage teachers’ careers – relates to teachers’ career self-management – i.e. teachers steering their careers by means of searching for opportunities, networking, or seeking supervisory support. Moreover, it examines the mediating roles of occupational self-efficacy and learning goal orientation in this relationship. Mediation analysis in SPSS, using the PROCESS macro of survey data from 220 Dutch secondary school teachers, showed that positive relationships between organizational career management and career self-management were mediated by occupational self-efficacy and learning goal orientation.     

The Relative Fit measure for evaluating a blockmodel

Statistical Methods & Applications - A blockmodel is a network in which the nodes are clusters of equivalent (in terms of the structure of the links connecting) nodes in the network being...