Titlebook: Computer Intensive Methods in Statistics; Wolfgang H?rdle,Léopold Simar Conference proceedings 1993 Springer-Verlag Berlin Heidelberg 1993

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書(shū)目名稱Computer Intensive Methods in Statistics讀者反饋




書(shū)目名稱Computer Intensive Methods in Statistics讀者反饋學(xué)科排名

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giggle

https://doi.org/10.1007/978-3-8348-9154-9f a computer program for use as a companion to the lectures. No satisfactory solution could be found from the existing commercial or public softwares. We discuss in detail some of the most salient features of the experiment and we describe the tools which the authors developed in the process.

progestin

Approximate HPD Regions for Testing Residual Autocorrelation Using Augmented Regressionspendent and explanatory variables, and requires numerical integration. The tests are evaluated through a small Monte-Carlo experiment, which indicates that the first test (easier to compute) is more powerful than the second one.

inculpate

Madrigal

Efficient Computer Generation of Matric-Variate , Drawings with an Application to Bayesian Estimatio. The different steps of the algorithm for matric-variate . drawings and the decomposition of the (inverted-) Wishart are explained. For illustrative purposes, the posterior density of the structural parameters of a simple market model is evaluated. These structural parameters are nonlinear functions of matric-variate . variables.

Madrigal

,Rohrstr?mung und Druckverlust,, noise filtering and discriminant analysis. For instance, we propose a Mrf model on the spectral signatures space, a strongly unified approach to classification and noise filtering as well as a particular model of noise.

CLAY

https://doi.org/10.1007/978-3-8348-9154-9estimate. Various techniques have been proposed in the past ten last years to select optimal values of this parameter. This paper presents a survey on theoretical results concerned with bandwidth selection.

lacrimal-gland

,Instation?re Str?mung in Rohrleitungen,. This is achieved by resampling methods. Different bootstrap and jackknife estimates are presented. The behaviour of these estimates are investigated on artificial data and on real data. The resulting choices are confronted with those given by na?ve rules.

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