Giampiero MARRA, Rosalba RADICE, Estimation of a semiparametric recursive bivariate probit model in the presence of endogeneity, The Canadian Journal of Statistics / La Revue Canadienne de Statistique ...

Huiping Xu, Bruce A. Craig, Likelihood Analysis of Multivariate Probit Models Using a Parameter Expanded MCEM Algorithm, Technometrics, Vol. 52, No. 3 (August 2010), pp. 340-348 ...

MICProB is composed of two nested probit regression models, where the inner model is estimated for predicting primary instances, which are considered as the “important” ones that determine the bag ...

The types of activation functions most often used in artificial neural networks are logistic and hyperbolic tangent. Activation functions used in ANN have been said to play an important role in the ...

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 of both.