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Empirical Likelihood Art B. Owen 9781584880714 Hardcover Buch-
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eBay-Artikelnr.:187255989100
Artikelmerkmale
- Artikelzustand
- ISBN 13
- 9781584880714
- ISBN
- 1584880716
- Field of Study
- Mathematics
- Educational Level
- College
- Level
- Intermediate
- Features
- 1st Edition
- Topic
- Statistics
Über dieses Produkt
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
1584880716
ISBN-13
9781584880714
eBay Product ID (ePID)
1777890
Product Key Features
Number of Pages
304 Pages
Language
English
Publication Name
Empirical Likelihood
Publication Year
2001
Subject
Mechanics / General, Probability & Statistics / General
Type
Textbook
Subject Area
Mathematics, Science
Series
Chapman and Hall/Crc Monographs on Statistics and Applied Probability Ser.
Format
Hardcover
Dimensions
Item Height
0.9 in
Item Weight
20 Oz
Item Length
9.3 in
Item Width
6.6 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2001-028680
Dewey Edition
21
Series Volume Number
92
Illustrated
Yes
Volume Number
Vol. 92
Dewey Decimal
519.5/44
Table Of Content
EMPIRICAL LIKELIHOOD (EL) Introduction Empirical Distribution Function Nonparametric Maximum Likelihood Nonparametric Likelihood Ratios Ties in the Data Multinomial on the Sample EL for a Univariate Mean Coverage Accuracy Power and Efficiency Empirical versus Parametric Inferences Computing the Empirical Likelihood EL FOR RANDOM VECTORS NPMLE for Random Vectors EL for a Multivariate Mean Fisher, Bartlett, and Bootstrap Calibration Smooth Functions of Means Estimating Equations Transformation Invariance of EL Using Side Information Convex dual Problem Unconstrained Dual Problem Solving the Dual Problem Euclidean Likelihood Other Nonparametric Likelihoods REGRESSION AND MODELING Sampling Pairs Fixed Regressors Triangular Array ELT Analysis of Variance Variance Modeling Nonlinear Least Squared Generalized Linear Models Generalized Projection Pursuit Plastic pipe Data Euclidean likelihood for Regression and ANOVA SYMMETRY AND INDEPENDENCE Testing Symmetry Constraining to Symmetry Approximate Symmetry Symmetric Unimodal Distributions Testing Independence Constraining to Independence Approximate Independence Permutation Tests IMPERFECTLY OBSERVED DATA Biased Sampling Truncation Multiple Biased Samples Censoring CURVE ESTIMATION Kernel Estimates Bias and Variance EL for Kernel Smooths Blood Pressure Trajectories Simultaneous Inference Bands for the ECDF Bands for the Quantile Function DEPENDENT DATA Reducing to Independence Blockwise Empirical Likelihood Hierarchical Data Dual likelihood for Martingales HYBRIDS AND CONNECTIONS Parametric Models for Subsets of Data Parametric Models for Components of the Data Parametric Models for Data Ranges Empirical Likelihood and Bayes Bayesian Bootstrap Nonparametric tilting Bootstrap Weighted Likelihood Bootstrap Bootstrap Likelihoods Jackknifes SOME PROOFS Lemmas Vector ELT Triangular Array ELT Multisample ELT ALGORITHMS Smooth Optimization Simple Hypotheses Composite Hypotheses Overdetermined NPMLE Constraints Partial Derivatives Nested Algorithms Gradient Equations Primal Problem Sequential Linearization Sequential Linearization and Estimating Equations Semi-infinite Programming Profiling Empirical Likelihoods HIGHER ORDER ASYMPTOTICS Bartlett Correction Pseudo-Likelihood Theory Signed Root Corrections Least Favorable Families Large Deviations
Synopsis
One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies the method to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Numerous examples from a variety of disciplines and detailed descriptions of algorithms-also posted on a companion Web site-illustrate the methods in practice., Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling. One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer visual reinforcement of the concepts and techniques. Examples from a variety of disciplines and detailed descriptions of algorithms-also posted on a companion Web site at-illustrate the methods in practice. Exercises help readers to understand and apply the methods. The method of empirical likelihood is now attracting serious attention from researchers in econometrics and biostatistics, as well as from statisticians. This book is your opportunity to explore its foundations, its advantages, and its application to a myriad of practical problems.
LC Classification Number
QA276.8.O94 2001
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