0

We propose a framework for out-of-sample predictive ability testing and forecast selection designed for use in the realistic situation in which the forecasting model is possibly misspecified, due to unmodeled dynamics, unmodeled heterogeneity, incorrect functional form, or any combination of these. Relative to the existing literature (Diebold and Mariano (1995) and West (1996)), we introduce tw...

This chapter provides an overview of pseudo-out-of-sample tests of unconditional predictive ability. We begin by providing an overview of the literature, including both empirical applications and theoretical contributions. We then delineate two distinct methodologies for conducting inference: one based on the analytics in West (1996) and the other based on those in Giacomini and White (2006). T...

In this paper we outline conditions under which the Diebold and Mariano (DM: 1995) test for predictive ability can be extended to the case of two forecasting models, each of which may include cointegrating relations, when allowing for parameter estimation error. We show that in the cases where either the loss function is quadratic or the length of the prediction period, P, grows at a slower rat...

results the command is addpred for logistic regression models. conclusions the stata package provided herein can encourage the use of novel methods in examining predictive capacity of ever-emerging plethora of novel biomarkers. materials and methods we have written a stata command that is intended to help researchers obtain cut point-free and cut point-based net reclassification improvement ind...

conclusions herein we have described the stata package “adpredsurv” for calculation of the nam-d’agostino x2 goodness of fit test as well as cut point-free and cut point-based nri, relative and absolute idi, and survival-based regression analyses. we hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers. background a fun...