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 ...

• 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 ...

In 1991, the A.M. Best Company changed the schedules and procedures for assigning ratings to property-liability insurers. An explanation of this change is of interest to consumers, regulators, and ...

The estimation of empirical models is essential to public policy analysis and social science research. Ordinary Least Squares (OLS) regression analysis is the most frequently used empirical model, and ...

We examine whether the adoption of information security measures can reduce the probability of computer virus infection by using firm-level survey data and probit regression analysis. We find that ...

Probit regression is very similar to logistic regression and the two techniques typically give similar results. Probit regression tends to be used most often with finance and economics data, but both ...