Search Results - subject:"Kullback–Leibler information"

Comparing the accuracy of multivariate density forecasts in selected regions of the copula support

Diks, Cees G. H.; Panchenko, Valentyn; Sokolinskiy, Oleg; … - In: Journal of economic dynamics & control 48 (2014), pp. 79-94

Persistent link: https://www.econbiz.de/10010485831

Model Selection in the Presence of Incidental Parameters

Lee, Yoonseok; Phillips, Peter C.B. - Center for Policy Research, Maxwell School - 2013

criteria are developed here that use either the Kullback-Leibler information criterion based on the profile likelihood or the …

Persistent link: https://www.econbiz.de/10010701001

Discrete approximations of continuous distributions by maximum entropy

Tanaka, Ken’ichiro; Toda, Alexis Akira - In: Economics Letters 118 (2013) 3, pp. 445-450

the principle of maximum entropy and minimum Kullback–Leibler information, which is computationally very simple. Our …

Persistent link: https://www.econbiz.de/10011041706

Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC

Hyndman, Rob L.; Zhang, Xibin; King, Maxwell L. - Econometric Society - 2004

Kullback-Leibler information criterion, and is as good as the plug-in algorithm under the mean integrated squared errors (MISE …

Persistent link: https://www.econbiz.de/10005702571

Density Estimation and Combination under Model Ambiguity

D'Amico, Stefania - Society for Computational Economics - SCE - 2004

This paper proposes a method for estimating the probability density of a variable of interest in the presence of model ambiguity. In the first step, each candidate parametric model is estimated minimizing the Kullback-Leibler "distance" (KLD) from a reference nonparametric density estimate....

Persistent link: https://www.econbiz.de/10005345310