Negative binomial loglinear mixed models with general random effects covariance matrix

Negative Binomial Loglinear Mixed Models

Beta - Binomial and Ordinal Joint Model with Random Effects for Analyzing Mixed Longitudinal Responses

The analysis of discrete mixed responses is an important statistical issue in various sciences. Ordinal and overdispersed binomial variables are discrete. Overdispersed binomial data are a sum of correlated Bernoulli experiments with equal success probabilities. In this paper, a joint model with random effects is proposed for analyzing mixed overdispersed binomial and ordinal longitudinal respo...

Bayesian Modeling of Random Effects Covariance Matrix for Generalized Linear Mixed Models

Generalized linear mixed models(GLMMs) are frequently used for the analysis of longitudinal categorical data when the subject-specific effects is of interest. In GLMMs, the structure of the random effects covariance matrix is important for the estimation of fixed effects and to explain subject and time variations. The estimation of the matrix is not simple because of the high dimension and the ...

Identifiability of Dynamic Stochastic General Equilibrium Models with Covariance Restrictions

This article is concerned with identification problem of parameters of Dynamic Stochastic General Equilibrium Models with emphasis on structural constraints, so that the number of observable variables is equal to the number of exogenous variables. We derived a set of identifiability conditions and suggested a procedure for a thorough analysis of identification at each point in the parameters sp...

determinant of the hankel matrix with binomial entries

abstract in this thesis at first we comput the determinant of hankel matrix with enteries a_k (x)=?_(m=0)^k??((2k+2-m)¦(k-m)) x^m ? by using a new operator, ? and by writing and solving differential equation of order two at points x=2 and x=-2 . also we show that this determinant under k-binomial transformation is invariant.