Least Squares Regressions with the Bootstrap

Name: Least Squares Regressions with the Bootstrap
Brand: Grin Verlag
SKU: 9783640421831
Price: 134.9 RON
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A Survey of their Performance

Autor: Jonas Böhmer

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Editura: Grin Verlag

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Diploma Thesis from the year 2009 in the subject Statistics, grade: 1,6, University of Bonn (Statist...

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Autor

Jonas Böhmer

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2009

Pagini

EAN

9783640421831

ISBN

3640421833

Enbook ID

01624746

Editura

Grin Verlag

Greutate

Dimensiuni

148 x 210 x 4

Descriere completă

Diploma Thesis from the year 2009 in the subject Statistics, grade: 1,6, University of Bonn (Statistische Abteilung der Rechts- und Staatswissenschaftlichen Fakultät), course: Diplomarbeit bei Prof.Dr. Alois Kneip, language: English, abstract: The statistical technique called bootstrap is usable with a lot of inferential problems and it is the main topic of this paper. Since the bootstrap provides material for a whole series of booksit is essential to pick one special aspect of the bootstrap and investigate it in depth, otherwise the analysis would inevitably become too general. This aspect is the topic of regression. Hence, this paper will introduce the bootstrap and compare the performance of the new inference methods which it provides with some classical methods of judging a regression which were used in the years before the bootstrap.Therefore the remainder of this paper is as follows: First there will be a description of the basic model in which all of the following investigations will be done, chapter two. The next chapter will describe the different regression techniques which try to solve the model.The fourth chapter is going to show the behavior of these regression techniques in large samples, i.e. shows some classical methods of statistical inference. Following chapter five will give an introduction to the bootstrap which will be succeeded by a description of the bootstrap in regression problems, chapter six. The seventh chapter will show how inference is done with the help of the bootstrap. The eighth chapter is going to compare theperformances of classical and bootstrap inference in regressions. Before the concluding remarks of chapter ten, there will be a practical application in chapter nine which tries to prove some observations of the preceeding chapters.

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Least Squares Regressions with the Bootstrap

A Survey of their Performance

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