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 ...

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 ...

In this paper, I introduce changepoint models for binary and ordered time series data based on Chib's hidden Markov model. The extension of the changepoint model to a binary probit model is ...

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.

The PROBIT procedure also performs logistic regression, and the LOGISTIC, GENMOD, and PROBIT procedures allow you to use events/trials input for the responses; the ratio of events to trials must be ...