Richard N. Rosett, Forrest D. Nelson, Estimation of the Two-Limit Probit Regression Model, Econometrica, Vol. 43, No. 1 (Jan., 1975), pp. 141-146 ...

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 ...

Probit ("probability unit") regression is a classical machine learning technique that can be used for binary classification -- predicting an outcome that can only be one of two discrete values. For ...

Example 45.3: Probit Model with Likelihood function The data, taken from Lee (1974), consist of patient characteristics and a variable indicating whether cancer remission occured.

A general log likelihood specification is used in the MODEL statement, and the RANDOM statement defines the random effect U to have standard deviation SD and subject variable SUB. The REPLICATE ...