Visual Studio Magazine

Probit Regression Using C#

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 ...
JSTOR Daily

Predicting Germination Response to Temperature. II. Three-dimensional Regression, Statistical Gridding and Iterative-probit Optimization Using Measured and Interpolated ...

• 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 ...
JSTOR Daily

Likelihood Inference in a Correlated Probit Regression Model

Equicorrelated binary observations are modelled using a multivariate probit regression model. Log likelihood derivatives are reduced to simple linear combinations of equicorrelated multivariate normal ...
Simon Fraser University

Analysis of Variance for Categorical Data and Generalized Linear Models

A categorical variable is defined as one that can assume only a limited number of values. For example, a person's sex is a categorical variable that can assume one of two values. Variables with levels ...
Simon Fraser University

Logistic Regression

You have many options for performing logistic regression in the SAS System. For the dichotomous outcome, most of the time you would use the LOGISTIC procedure or the GENMOD procedure; you will need to ...