Several model-based seasonal adjustment diagnostics are currently being incorporated into X-13-ARIMASEATS, a new hybrid seasonal adjustment program under development at the U.S. Census Bureau. These diagnostics have been implemented in the Ox programming language, and this paper discusses various aspects of the implementation. The diagnostics are normalized quadratic forms in the data, and roug...

Abstract: Modeling diagnostics assess models by means of a variety of criteria. Each criterion typically performs its evaluation upon a specific inferential objective. For instance, the well-known DFBETAS in linear regression models are a modeling diagnostic which is applied to discover the influential cases in fitting a model. To facilitate the evaluation of generalized linear mixed models (GL...

Assessing fit of psychometric models has always been an issue of enormous interest, but there exists no unanimously agreed upon item fit diagnostic for the models. Bayesian networks, frequently used in educational assessments (see, for example, Mislevy, Almond, Yan, & Steinberg, 2001) primarily for learning about students’ knowledge and skills, are no exception. This paper employs the posterior...

for effective crisis management, appropriate telecommunications, which are required to fast response, are crucial. therefore, lack of existing proper telecommunications detract senior managers’ awareness about crisis conditions and also disturb rescuers in relief, causing increasing attendance time to the injured and fatalities. transfer point location problem is one of the new issues in the li...

in this study, an effort has been made to determine the most important risk factors of tuberculosis (tb) in district mardan. a total of 645 cases were examined, and their personal and medical data were collected. for each case, the phenomenon of tb was studied in relation to different risk factors. statistical techniques of logistic regression and backward elimination procedure were used to ana...

Abstract It is often possible to describe the correct functioning of a system by a mathematical model. As long as observations or measurements correspond to the predictions made by the model, the system may be assumed to be functioning correctly. When, however, a discrepancy arises between the observations and the model-based predictions, then an explanation for this fact has to be found. The f...

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...