๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Bootstrap Approximation to the Distribution of M-estimates in a Linear Model

โœ Scribed by Xiao Ming Wang; Wang Zhou


Publisher
Institute of Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society
Year
2004
Tongue
English
Weight
194 KB
Volume
20
Category
Article
ISSN
1439-7617

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Approximate estimation in generalized li
โœ M.L. Feddag; M. Mesbah ๐Ÿ“‚ Article ๐Ÿ“… 2006 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 590 KB

This article discusses two different approaches to estimate the difficulty parameters (fixed effects parameters) and the variance of latent traits (variance components) in the mixed Ranch model. The first one is the generalized estimating equations (GEE2) which uses an approximation of the marginal

A bootstrap approximation to the joint d
โœ G. Mathew; W.P. McCormick ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 113 KB

This paper establishes the asymptotic validity for the moving block bootstrap as an approximation to the joint distribution of the sum and the maximum of a stationary sequence. An application is made to statistical inference for a positive time series where an extreme value statistic and sample mean