💥An Introduction to the Bootstrap Tibshirani R.J Free Fast Shipping

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Características del artículo

Estado
En buen estado: Libro que se ha leído pero que está en buen estado. Daños mínimos en la tapa, ...
Artist
Tibshirani, R.J.
Brand
N/A
Date of Publication
19940515
EAN
9780412042317
ISBN
0412042312
Book Title
An Introduction to the Bootstrap (Monographs on Statistics and...
Release Title
An Introduction to the Bootstrap (Monographs on Statistics and...
Colour
N/A
Categoría

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Product Identifiers

Publisher
CRC Press LLC
ISBN-10
0412042312
ISBN-13
9780412042317
eBay Product ID (ePID)
1351610

Product Key Features

Number of Pages
456 Pages
Language
English
Publication Name
Introduction to the Bootstrap
Subject
Probability & Statistics / General
Publication Year
1994
Type
Textbook
Subject Area
Mathematics
Author
Bradley Efron, R. J. Tibshirani
Series
Chapman and Hall/Crc Monographs on Statistics and Applied Probability Ser.
Format
Hardcover

Dimensions

Item Height
1.2 in
Item Weight
20.4 Oz
Item Length
9 in
Item Width
6.5 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
93-004489
TitleLeading
An
Dewey Edition
20
Grade From
College Freshman
Series Volume Number
57
Volume Number
Vol. 57
Illustrated
Yes
Dewey Decimal
519.544
Table Of Content
Introduction The Accuracy of a Sample Mean Random Samples and Probabilities The Empirical Distribution Function and the Plug-In Principle Standard Errors and Estimated Standard Errors The Bootstrap Estimate of Standard Error Bootstrap Standard Errors: Some Examples More Complicated Data Structures Regression Models Estimates of Bias The Jackknife Confidence Intervals Based on Bootstrap "Tables" Confidence Intervals Based on Bootstrap Percentiles Better Bootstrap Confidence Intervals Permutation Tests Hypothesis Testing with the Bootstrap Cross-Validation and Other Estimates of Prediction Error Adaptive Estimation and Calibration Assessing the Error in Bootstrap Estimates A Geometrical Representation for the Bootstrap and Jackknife An Overview of Nonparametric and Parametric Inference Further Topics in Bootstrap Confidence Intervals Efficient Bootstrap Computations Approximate Likelihoods Bootstrap Bioequivalence Discussion and Further Topics Appendix: Software for Bootstrap Computations References
Synopsis
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets., An Introduction to the Bootstrap arms scientists and engineers as well as statisticians with the computational techniques they need to analyze and understand complicated data sets. The bootstrap is a computer-based method of statistical inference that answers statistical questions without formulas and gives a direct appreciation of variance, bias, coverage, and other probabilistic phenomena. This book presents an overview of the bootstrap and related methods for assessing statistical accuracy, concentrating on the ideas rather than their mathematical justification. Not just for beginners, the presentation starts off slowly, but builds in both scope and depth to ideas that are quite sophisticated.

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