IEEE

Spatial probit regression model: Recursive importance sampling approach

Abstract: The probit regression model is a model used to analyze the relationship between categorical response variables, with predictive variables that are numerical, categorical, or the combination ...
JSTOR Daily

An Augmented Probit Model for Missing Predictable Covariates in Quantal Bioassay with Small Sample Size

This is a preview. Log in through your library . Abstract Quantal bioassay experiments relate the amount or potency of some compound; for example, poison, antibody, or drug to a binary outcome such as ...
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 ...
Simon Fraser University

Comparison of CATMOD, GENMOD, LOGISTIC, and PROBIT Procedures

The LOGISTIC, GENMOD, PROBIT, and CATMOD procedures can all be used for statistical modeling of categorical data. The CATMOD procedure provides maximum likelihood estimation for logistic regression, ...