Estimation Methods for the Multivariate t Distribution

Robust Factor Analysis Using the Multivariate t-Distribution

Factor analysis is a standard method for multivariate analysis. The sampling model in the most popular factor analysis is Gaussian and has thus often been criticized for its lack of robustness. A simple robust extension of the Gaussian factor analysis model is obtained by replacing the multivariate Gaussian distribution with a multivariate t-distribution. We develop computational methods for bo...

Two-stage estimation using copula function

‎Maximum likelihood estimation of multivariate distributions needs solving a optimization problem with large dimentions (to the number of unknown parameters) but two‎- ‎stage estimation divides this problem to several simple optimizations‎. ‎It saves significant amount of computational time‎. ‎Two methods are investigated for estimation consistency check‎. ‎We revisit Sankaran and Nair's bivari...

Screening for a Multivariate Mixture Normal Distribution

Modelling of Correlated Ordinal Responses, by Using Multivariate Skew Probit with Different Types of Variance Covariance Structures

In this paper, a multivariate fundamental skew probit (MFSP) model is used to model correlated ordinal responses which are constructed from the multivariate fundamental skew normal (MFSN) distribution originate to the greater flexibility of MFSN. To achieve an appropriate VC structure for reaching reliable statistical inferences, many types of variance covariance (VC) structures are considered ...

Estimation of Evolution of Relative Humidity Distribution for Concrete Slabs

Realistic prediction of concrete shrinkage and creep requires the calculation of the distributions of relative humidity at various times. Although the distributions of the relative humidity can be computed by numerical methods from the differential equation for diffusion, simple prediction formulas can facilitate structural analysis. The purpose of this paper is to present a simple formula for ...