Predictive Density Evaluation
نویسندگان
چکیده
منابع مشابه
Predictive Density Evaluation∗
This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and Diebold (2000), Diebold, Gunther and Tay (1998), Diebold, Hahn and Tay (1999), White (2000), Bai (2003...
متن کاملAdmissible Predictive Density Estimation
Let X|μ ∼ Np(μ,vxI ) and Y |μ ∼ Np(μ,vyI ) be independent pdimensional multivariate normal vectors with common unknown mean μ. Based on observing X = x, we consider the problem of estimating the true predictive density p(y|μ) of Y under expected Kullback–Leibler loss. Our focus here is the characterization of admissible procedures for this problem. We show that the class of all generalized Baye...
متن کاملPredictive Density Accuracy Tests∗
This paper outlines a testing procedure for assessing the relative out-of-sample predictive accuracy of multiple conditional distribution models, and surveys existing related methods in the area of predictive density evaluation, including methods based on the probability integral transform and the Kullback-Leibler Information Criterion. The procedure is closely related to Andrews’ (1997) condit...
متن کاملPredictive Density Estimation for Multiple Regression
Suppose we observe X ∼ Nm(Aβ, σI) and would like to estimate the predictive density p(y | β) of a future Y ∼ Nn(Bβ, σI). Evaluating predictive estimates p̂(y | x) by KullbackLeibler loss, we develop and evaluate Bayes procedures for this problem. We obtain general sufficient conditions for minimaxity and dominance of the “noninformative” uniform prior Bayes procedure. We extend these results to ...
متن کاملDisagreement, Uncertainty and the True Predictive Density
This paper generalizes the discussion about disagreement versus uncertainty in macroeconomic survey data by emphasizing the importance of the (unknown) true predictive density. Using a forecast combination approach, we ask whether crosssections of survey point forecasts help to approximate the true predictive density. We find that although these cross-sections perform poorly individually, their...
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ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2005
ISSN: 1556-5068
DOI: 10.2139/ssrn.812104