Multivariate binary data arise in a variety of settings. In this article we propose a practical and efficient computational framework for maximum likelihood estimation of multivariate probit ...

We’ll use the R software language to run some examples of multiple linear regression and probit regression using the bayesm package that will illustrate these concepts. Hopefully you'll come away with ...

The LOGISTIC, GENMOD, PROBIT, and CATMOD procedures can all be used for statistical modeling of categorical data. The CATMOD procedure provides maximum likelihood estimation for logistic regression, ...

Zhenyu Zhang, Akihiko Nishimura, Paul Bastide, Xiang Ji, Rebecca P. Payne, Philip Goulder, Philippe Lemey, Marc A. Suchard, LARGE-SCALE INFERENCE OF CORRELATION AMONG MIXED-TYPE BIOLOGICAL TRAITS WITH ...

In addition, PROC GLM allows only one model and fits the full model. See Chapter 4, "Introduction to Analysis-of-Variance Procedures," and Chapter 30, "The GLM Procedure," for more details. The CATMOD ...

When presented with a binary classification problem, a common strategy is to try probit or logistic regression first. If the resulting model is not satisfactory then you can try a neural model and use ...