Weak Convergence Of The Log Likelihood Process In The Two Phase Linear Regression Problem PDF Download

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Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80th Birthday

Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80th Birthday
Author: Francisco J Samaniego
Publisher: World Scientific
Total Pages: 479
Release: 2011-09-16
Genre: Mathematics
ISBN: 9814458171

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This volume consists of 22 research papers by leading researchers in Probability and Statistics. Many of the papers are focused on themes that Professor Bhattacharya has published on research. Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory.This volume presents state-of-the-art research in statistical theory, with an emphasis on nonparametric inference, linear model theory, time series analysis and asymptotic theory. It will serve as a valuable reference to the statistics research community as well as to practitioners who utilize methodology in these areas of emphasis.


Change-point Problems

Change-point Problems
Author: Edward G. Carlstein
Publisher: IMS
Total Pages: 400
Release: 1994
Genre: Mathematics
ISBN: 9780940600348

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Asymptotic Theory in Probability and Statistics with Applications

Asymptotic Theory in Probability and Statistics with Applications
Author: T. L. Lai
Publisher:
Total Pages: 560
Release: 2008
Genre: Mathematics
ISBN:

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Presents a collection of 18 papers, many of which are surveys, on asymptotic theory in probability and statistics, with applications to a variety of problems. This volume comprises three parts: limit theorems, statistics and applications, and mathematical finance and insurance. It is suitable for graduate students in probability and statistics.


Local Regression and Likelihood

Local Regression and Likelihood
Author: Clive Loader
Publisher: Springer Science & Business Media
Total Pages: 290
Release: 2006-05-09
Genre: Mathematics
ISBN: 0387227326

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Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, with extensions to local likelihood and density estimation. Practical information is also included on how to implement these methods in the programs S-PLUS and LOCFIT.