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We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation...
Persistent link: https://www.econbiz.de/10009642530
This article examines the notion of distortion of copulas, a natural extension of distortion within the univariate framework. We study three approaches to this extension: (1) distortion of the margins alone while keeping the original copula structure, (2) distortion of the margins while...
Persistent link: https://www.econbiz.de/10008596415
We propose two simple evaluation methods for time-varying density forecasts of continuous higher-dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation...
Persistent link: https://www.econbiz.de/10010577340
Density forecast (DF) possesses appealing properties when it is correctly specified for the true conditional distribution. Although a number of parametric specification tests have been introduced for the DF evaluation (DFE) in the parameter-free context, econometric DF models are typically...
Persistent link: https://www.econbiz.de/10009146881
. We work with the one-step-ahead quantile residuals, which must be i.i.d. (univariate and multivariate) normal under the …
Persistent link: https://www.econbiz.de/10011051448
Developing sound or reliable statistical models for analyzing vehicle crashes is veryimportant in highway safety studies. A difficulty arises when crash data exhibit overdispersion.Over-dispersion caused by unobserved heterogeneity is a serious problemand has been addressed in a variety ways...
Persistent link: https://www.econbiz.de/10009464902
In this thesis, we propose to analyze panel count data using a spline-basedsieve generalized estimating equation method with a semiparametric proportional mean model E(N(t)|Z) = Λ0(t) eβT0Z. The natural log of the baseline mean function, logΛ0(t), is approximated by a monotone cubic B-spline...
Persistent link: https://www.econbiz.de/10009466051