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 ...

and is the normal probability function. This is the likelihood function for a binary probit model. This likelihood is strictly positive so that you can take a square root of and use this as your ...

• Background and Aims Most current thermal-germination models are parameterized with subpopulation-specific rate data, interpolated from cumulative-germination-response curves. The purpose of this ...

The data for this example are from Ezzet and Whitehead (1991), who describe a crossover experiment on two groups of patients using two different inhaler devices (A and B). Patients from group 1 used ...