Stepwise Regression - a standard linear regression with stepwise selection of predictors.
Logistic Regression - binary logistic regression.
Local Geographic Regression - Estimates one regression for each data point, using data from its nearest-K neighbors (you must have geo-codes for each data point)
Univariate PLS Regression - space reduction for a set of predictors while maximizing their fit to a continuous dependent variable.
Multivariate PLS Regression - as extension of PLS Regression, for explaining multiple dependent variables using a set of predictors.
Mixture Logit - random-coefficients Multinomial Logit choice model, producing individual-level estimates for the response coefficients.
Stochastic Frontier Regression - linear regression with asymmetric errors; the regression line is fitted around the top or bottom of the cloud of points.
Qualitative Data Envelopment Analysis - very flexible DEA tool that allows for qualitative inputs and outputs.
Sliced Average Variance Estimation - space-reduction for a set of predictors while maximizing the fit to a binary dependent variable.
Predictive Stepwise Linear Regression - stepwise predictor selection in a Linear Regression to maximize predictive fit in hold-out samples, rather than calibration fit
Predictive Stepwise Logistic Regression – stepwise predictor selection in a Binary Logistic Regression to maximize predictive fit in hold-out samples.