Quantile regression (QR) models are one of the methods for longitudinal data analysis. When responses seemto be skew and asymmetric due to outliers heavy-tails, QR may work suitably. This paper developes semi-parametric quantile model analyzing continuous ordinal mixed responses. The latent variable some threshold parameters used perform model’s part. error has Asymmetric Laplace (AL) distribut...

financial companies are constantly exposed to the dangers of risk. in the last few years for various reasons, measuring value at risk (var) has become increasingly important for financial firms. the study of multiple measures of risk, var measure with a new approach provides the ground for calculation of market risk. common approaches to risk measurement due to complicated, nonlinear and changi...

Nowadays, one of the most important topics in risk management of banks, financial, and credit institutions is credit risk management. In this research, the researchers used survival analytic methods for credit risk modeling in terms of the conditional distribution function of default time. As a practical task, the authors considered the reward credit portfolio of Tose'e Ta'avon Bank of Guilan P...

Adaptive robust control (ARC) of MIMO nonlinear systems transformable to two semi-strict feedback forms are considered. The forms can have both parametric uncertainties and uncertain nonlinearities such as external disturbances. In addition, the forms allow coupling and appearance of parametric uncertainties in the input matrix of each layer. Furthermore, the usual assumption on the linear para...

In clinical trials examining the incidence of pneumonia it is a common practice to measure infection via both invasive and non-invasive procedures. In the context of a recently completed randomized trial comparing two treatments the invasive procedure was only utilized in certain scenarios due to the added risk involved, and given that the level of the non-invasive procedure surpassed a given t...

The linear mixed model (LMM) is a popular statistical for the analysis of longitudinal data. However, robust estimation and inferential conclusions LMM in presence outliers (i.e., observations with very low probability occurrence under Normality) not part mainstream data analysis. In this work, we compared coverage rates confidence intervals (CIs) ba...

This article presents a general approach for logit random effects modelling of clustered ordinal and nominal responses. We review multinomial logit random effects models in a unified form as multivariate generalized linear mixed models. Maximum likelihood estimation utilizes adaptive Gauss–Hermite quadrature within a quasi-Newton maximization algorithm. For cases in which this is computationall...