Subset Selection in Regression

Subset Selection in Regression

Author: Alan Miller

Publisher: CRC Press

Published: 2002-04-15

Total Pages: 258

ISBN-13: 1420035932

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Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author ha


Simultaneous Statistical Inference

Simultaneous Statistical Inference

Author: Rupert G. Jr. Miller

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 311

ISBN-13: 1461381223

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Simultaneous Statistical Inference, which was published originally in 1966 by McGraw-Hill Book Company, went out of print in 1973. Since then, it has been available from University Microfilms International in xerox form. With this new edition Springer-Verlag has republished the original edition along with my review article on multiple comparisons from the December 1977 issue of the Journal of the American Statistical Association. This review article covered developments in the field from 1966 through 1976. A few minor typographical errors in the original edition have been corrected in this new edition. A new table of critical points for the studentized maximum modulus is included in this second edition as an addendum. The original edition included the table by K. C. S. Pillai and K. V. Ramachandran, which was meager but the best available at the time. This edition contains the table published in Biometrika in 1971 by G. 1. Hahn and R. W. Hendrickson, which is far more comprehensive and therefore more useful. The typing was ably handled by Wanda Edminster for the review article and Karola Decleve for the changes for the second edition. My wife, Barbara, again cheerfully assisted in the proofreading. Fred Leone kindly granted permission from the American Statistical Association to reproduce my review article. Also, Gerald Hahn, Richard Hendrickson, and, for Biometrika, David Cox graciously granted permission to reproduce the new table of the studentized maximum modulus. The work in preparing the review article was partially supported by NIH Grant ROI GM21215.


Simultaneous Inference in Regression

Simultaneous Inference in Regression

Author: Wei Liu

Publisher: CRC Press

Published: 2010-10-19

Total Pages: 292

ISBN-13: 9781439828106

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Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. Simultaneous Inference in Regression provides a thorough overview of the construction methods and applications of simultaneous confidence bands for various inferentia


Optimal Subset Selection

Optimal Subset Selection

Author: David Boyce

Publisher: Springer Science & Business Media

Published: 2013-03-08

Total Pages: 203

ISBN-13: 3642463118

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In the course of one's research, the expediency of meeting contractual and other externally imposed deadlines too often seems to take priority over what may be more significant research findings in the longer run. Such is the case with this volume which, despite our best intentions, has been put aside time and again since 1971 in favor of what seemed to be more urgent matters. Despite this delay, to our knowledge the principal research results and documentation presented here have not been superseded by other publications. The background of this endeavor may be of some historical interest, especially to those who agree that research is not a straightforward, mechanistic process whose outcome or even direction is known in ad vance. In the process of this brief recounting, we would like to express our gratitude to those individuals and organizations who facilitated and supported our efforts. We were introduced to the Beale, Kendall and Mann algorithm, the source of all our efforts, quite by chance. Professor Britton Harris suggested to me in April 1967 that I might like to attend a CEIR half-day seminar on optimal regression being given by Professor M. G. Kendall in Washington. D. C. I agreed that the topic seemed interesting and went along. Had it not been for Harris' suggestion and financial support, this work almost certainly would have never begun.


Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Author: Chester Ismay

Publisher: CRC Press

Published: 2019-12-23

Total Pages: 461

ISBN-13: 1000763463

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.


Applied Stochastic Models And Data Analysis - Proceedings Of The Fifth International Symposium On Asmda

Applied Stochastic Models And Data Analysis - Proceedings Of The Fifth International Symposium On Asmda

Author: Valderrama M J

Publisher: #N/A

Published: 1991-03-29

Total Pages: 672

ISBN-13: 9814556297

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As with previous symposiums, the main objective of the Sixth International Symposium is to publish papers (of both technical and practical nature) to present new findings uncovered by theoretical results which may have the potential to contribute solutions to real-life problems. With this objective in mind, this collection of papers aims to serve as an interface between stochastic modeling and data analysis as well as their applications to the problems we face in the various fields. The papers first focused on the theory, application and interaction between stochastic models and data analysis. The results and their applications to the problems we face in the fields of economics, finance and insurance, management, marketing, health sciences, production and engineering are then explored.


Statistical Data Analysis and Inference

Statistical Data Analysis and Inference

Author: Y. Dodge

Publisher: Elsevier

Published: 2014-05-23

Total Pages: 630

ISBN-13: 1483296113

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A wide range of topics and perspectives in the field of statistics are brought together in this volume. The contributions originate from invited papers presented at an international conference which was held in honour of C. Radhakrishna Rao, one of the most eminent statisticians of our time and a distinguished scientist.


Polarimetric Detection, Characterization and Remote Sensing

Polarimetric Detection, Characterization and Remote Sensing

Author: Michael I. Mishchenko

Publisher: Springer Science & Business Media

Published: 2011-05-29

Total Pages: 573

ISBN-13: 9400716354

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As the need for accurate and non-invasive optical characterization and diagnostic techniques is rapidly increasing, it is imperative to find improved ways of extracting the additional information contained within the measured parameters of the scattered light. This is the first specialized monograph on photopolarimetry, a rapidly developing, multidisciplinary topic with numerous military, ecological remote-sensing, astrophysical, biomedical, and technological applications. The main objective is to describe and discuss techniques developed in various disciplines to acquire useful information from the polarization signal of scattered electromagnetic waves. It focuses on the state-of-the-art in polarimetric detection, characterization, and remote sensing, including military and environmental monitoring as well as terrestrial, atmospheric, and biomedical characterization. The book identifies polarimetric techniques that have been especially successful for various applications as well as the future needs of the various research communities. The monograph is intended to facilitate cross-pollination of ideas and thereby improve research efficiency and help advance the field of polarimetry into the future. The book is thoroughly interdisciplinary and contains only invited review chapters written by leading experts in the respective fields. It will be useful to science professionals, engineers, and graduate students working in a broad range of disciplines: optics, electromagnetics, atmospheric radiation and remote sensing, radar meteorology, oceanography, climate research, astrophysics, optical engineering and technology, particle characterization, and biomedical optics.