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term in the multivariate linear regression model. The nonparametric part of the method treats the marginal distributions of …. It turns out that there is no loss of asymptotic efficiency due to the estimation of the regression parameters. An … Ritz (2000) for the multivariate regression model. …
Persistent link: https://www.econbiz.de/10005125276
This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the...
Persistent link: https://www.econbiz.de/10005149031
We present a local linear estimator with variable bandwidth for multivariate nonparametric regression. We prove its … to obtain practical direct plug-in bandwidth selectors for heteroscedastic regression in one and two dimensions. We show …
Persistent link: https://www.econbiz.de/10005149087
combines simulation with nonparametric regression in the computation of GMM models. We provide formal conditions under which … this setting, local linear kernel regression methods have theoretical advantages over local kernel methods that are also …
Persistent link: https://www.econbiz.de/10011093867
The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups. We introduce a new method for selecting bandwidths when computing kernel estimates of ROC curves. Our technique allows for interaction between...
Persistent link: https://www.econbiz.de/10005149070
A new simple formula is found to correct the underestimation of the standard deviation for total lead time demand when using simple exponential smoothing. This new formula allows one to see readily the significant size of the underestimation of the traditional formula and can easily be...
Persistent link: https://www.econbiz.de/10005149115
asymptotic approximation, rather than a more sophisticated approach using the bootstrap, since the latter requires a multiplicity …
Persistent link: https://www.econbiz.de/10005427623
The problem considered in this paper is how to find reliable prediction intervals with simple exponential smoothing and trend corrected exponential smoothing. Methods for constructing prediction intervals based on linear approximation and bootstrapping are proposed.
Persistent link: https://www.econbiz.de/10005087580
This paper derives six different forms of message length functions for general linear regression model. In so doing …
Persistent link: https://www.econbiz.de/10005087586
It is well known that the usual techniques for estimating random and fixed effects panel data models are inconsistent in the dynamic setting. As a consequence, numerous consistent estimators have been proposed in the literature. However, all such estimators rely on certain well defined...
Persistent link: https://www.econbiz.de/10005087599