When Does Bootstrap Work?

Name: When Does Bootstrap Work?
Brand: Springer-Verlag New York Inc.
SKU: 9780387978673
Price: 126.35 EUR
Availability: InStock

Asymptotic Results and Simulations

Автор: Enno Mammen

Език:

Корици: С меки корици

Издател: Springer-Verlag New York Inc.

Наличност: Външен склад

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In these notes some results are presented for the asymptotic behavior of the bootstrap procedure. Bo...

Информация за книгата

Автор

Enno Mammen

Език

Английски език

Корици

Книга - С меки корици

Издадена

1992

страници

201

EAN

9780387978673

ISBN

0387978674

Enbook ID

06793984

Издател

Springer-Verlag New York Inc.

Теглоt

330

Размери

155 x 235 x 12

Пълно описание

In these notes some results are presented for the asymptotic behavior of the bootstrap procedure. Bootstrap is a procedure for estimating (approximating) the distribution of a statistic. It is based on resampling and simulations. It was been introduced in Efron (1979) and in the last decade it has been discussed for a wide variety of statistical problems. Introductory are the articles Efron and Gong (1983) and Efron and Tibshirani (1986) and the book Helmers (1991b). Many applications of bootstrap are discussed in Efron (1982). Survey articles are Beran (1984b), Hinkley (1988), and Diciccio and Romano (1988a). For many classical decision problems (testing and estimation problems, prediction, construction of confidence regions) bootstrap has been compared with classical approximations based on mathematical limit theorems and expansions (for instance normal approximations, empirical Edgeworth expansions) (see for instance Bretagnolle (1983) and Beran (1982, 1984a, 1987, 1988), Abramovitch and Singh (1985), and Hall (1986a, 1988) ). An asymptotic treatment of bootstrap is contained in the book Beran and Ducharme (1991). A detailed analysis of bootstrap based on higher order Edgeworth expansions has been carried out in the book Hall (1992). Recent publications on bootstrap can also be found in the conference volumes LePage and Billard (1992) and Joeckel, Rothe, and Sendler (1992). We will consider the application of bootstrap in three contexts : estimation of smooth functionals, nonparametric curve estimation, and linear models. We do not attempt a complete description of bootstrap in these areas.

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When Does Bootstrap Work?

Asymptotic Results and Simulations

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