This study predicts stock splits using two ensemble machine learning techniques: gradient boosting machines (GBMs) and random forests (RFs). The goal is to form implementable portfolios based on positive predictions to generate abnormal returns. Since splits are rare events, we use SMOTE...

The finite sample performance of a number of linear regression estimators is investigated in a variety of parametric settings involving outliers. A Bayesian approach is shown to have good overall comparative performance. It is then shown how the same Bayesian methodology can be easily extended...

We present a new Stata estimation program, mboxcox, that computes the normalizing scaled power transformations for a set of variables. The multivari- ate Box–Cox method (defined in Velilla, 1993, Statistics and Probability Letters 17: 259–263; used in Weisberg, 2005, Applied Linear Regression...

We present a new Stata command, irp, that generates the inverse response plot (Cook and Weisberg, 1994, Biometrika 81: 731–737) of a response on its predictors. Using the inverse response plot, an appropriate scaled power transformation for the positive response variable can be found so that...

We present a new Stata command, mmp, that generates marginal model plots (Cook and Weisberg, 1997, Journal of the American Statistical Association 92: 490–499) for a regression model. These plots allow for the comparison of the fitted model with a nonparametric or semiparametric model fit. The...

The sliced mean variance–covariance inverse regression (SMVCIR) algorithm takes grouped multivariate data as input and transforms it to a new coordinate system where the group mean, variance, and covariance differences are more apparent. Other popular algorithms used for performing graphical...

We present a new Stata program, vselect, that helps users perform variable selection after performing a linear regression. Options for stepwise meth- ods such as forward selection and backward elimination are provided. The user may specify Mallows’s Cp, Akaike’s information criterion,...