Predictive Likelihood

Sensitivity, specificity, predictive values, and likelihood ratios.

Shrinkage and Penalized Likelihood as Methods to Improve Predictive Accuracy

Hans C. van Houwelingen Saskia le Cessie Department of Medical Statistics, Leiden, The Netherlands P.O.Box 9604 2300 RC Leiden, The Netherlands email: [email protected] Abstract A review is given of shrinkage and penalization as tools to improve predictive accuracy of regression models. The James-Stein estimator is taken as starting point. Procedures covered are the Pre-test Estimation, ...

Predictive Likelihood Comparisons with DSGE and DSGE-VAR Models

In this paper we treat the issue of forecasting with DSGE and DSGE-VAR models, with particular attention to Bayesian estimation of the predictive distribution and its mean and covariance. As a novel contribution to the forecasting literature, which extends beyond (log-linearized) DSGE models and DSGE-VARs, we show how the value of the h-step-ahead marginal and joint predictive likelihood for a ...

Distance Enhancing Constraints for Noise Predictive Maximum Likelihood Detectors

|Using performance analysis of Reduced State Sequence Estimators (RSSE), we characterize dominant error events for a Noise Predictive Maximum Likelihood (NPML) detector. The error event characterization may be used to determine distance enhancing constraints that improve the reliability of NPML/RSSE detection. An example of a constraint that provides approximately :8 dB asymptotic coding gain f...

Improving medical predictive models via Likelihood Gamble Pricing

A combination of radiotherapy and chemotherapy, is often the treatment of choice for cancer patients. Recent developments in the treatment of patients have lead to improved survival. However, traditionally used clinical variables have poor accuracy for the prediction of survival and radiation treatment side effects. The objective of this work is to develop and validate improved predictive model...