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On Nonparametric Estimation And Inference With Censored Data Bandwidth Selection For Local Polynomial Regression And Subset Selection In Explanatory Regression Analyses
Download On Nonparametric Estimation And Inference With Censored Data Bandwidth Selection For Local Polynomial Regression And Subset Selection In Explanatory Regression Analyses full books in PDF, epub, and Kindle. Read online On Nonparametric Estimation And Inference With Censored Data Bandwidth Selection For Local Polynomial Regression And Subset Selection In Explanatory Regression Analyses ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis On Nonparametric Estimation and Inference with Censored Data, Bandwidth Selection for Local Polynomial Regression, and Subset Selection in Explanatory Regression Analyses by : Derick Randall Peterson
Download or read book On Nonparametric Estimation and Inference with Censored Data, Bandwidth Selection for Local Polynomial Regression, and Subset Selection in Explanatory Regression Analyses written by Derick Randall Peterson and published by . This book was released on 1998 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis State of the Art in Probability and Statistics by : Mathisca de Gunst
Download or read book State of the Art in Probability and Statistics written by Mathisca de Gunst and published by IMS. This book was released on 2001 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Local Polynomial Modelling and Its Applications by : Jianqing Fan
Download or read book Local Polynomial Modelling and Its Applications written by Jianqing Fan and published by Routledge. This book was released on 2018-05-02 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression.
Book Synopsis A Practical Introduction to Regression Discontinuity Designs by : Matias D. Cattaneo
Download or read book A Practical Introduction to Regression Discontinuity Designs written by Matias D. Cattaneo and published by Cambridge University Press. This book was released on 2024-04-11 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this Element, which continues our discussion in Foundations, the authors provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. The focus is on extensions to the canonical sharp RD setup that we discussed in Foundations. The discussion covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.
Book Synopsis Nonparametric Estimation and Regression Analysis with Left Truncated and Right Censored Data by : Stanford University. Dept. of Statistics
Download or read book Nonparametric Estimation and Regression Analysis with Left Truncated and Right Censored Data written by Stanford University. Dept. of Statistics and published by . This book was released on 1994 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Regression and Spline Smoothing, Second Edition by : Randall L. Eubank
Download or read book Nonparametric Regression and Spline Smoothing, Second Edition written by Randall L. Eubank and published by CRC Press. This book was released on 1999-02-09 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.
Book Synopsis Nonparametric Regression for Censored and Truncated Data by : Chul-Ki Kim
Download or read book Nonparametric Regression for Censored and Truncated Data written by Chul-Ki Kim and published by . This book was released on 1995 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Local Regression and Likelihood by : Clive Loader
Download or read book Local Regression and Likelihood written by Clive Loader and published by Springer Science & Business Media. This book was released on 2006-05-09 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Subset Selection in Regression by : Alan Miller
Download or read book Subset Selection in Regression written by Alan Miller and published by CRC Press. This book was released on 2002-04-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis A Distribution-Free Theory of Nonparametric Regression by : László Györfi
Download or read book A Distribution-Free Theory of Nonparametric Regression written by László Györfi and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Book Synopsis Applied Nonparametric Regression by : Wolfgang Härdle
Download or read book Applied Nonparametric Regression written by Wolfgang Härdle and published by Cambridge University Press. This book was released on 1990 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.
Book Synopsis Introduction to Nonparametric Regression by : K. Takezawa
Download or read book Introduction to Nonparametric Regression written by K. Takezawa and published by John Wiley & Sons. This book was released on 2005-12-02 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides an excellent introduction to the field for novices of nonparametric regression. Introduction to Nonparametric Regression clearly explains the basic concepts underlying nonparametric regression and features: * Thorough explanations of various techniques, which avoid complex mathematics and excessive abstract theory to help readers intuitively grasp the value of nonparametric regression methods * Statistical techniques accompanied by clear numerical examples that further assist readers in developing and implementing their own solutions * Mathematical equations that are accompanied by a clear explanation of how the equation was derived The first chapter leads with a compelling argument for studying nonparametric regression and sets the stage for more advanced discussions. In addition to covering standard topics, such as kernel and spline methods, the book provides in-depth coverage of the smoothing of histograms, a topic generally not covered in comparable texts. With a learning-by-doing approach, each topical chapter includes thorough S-Plus? examples that allow readers to duplicate the same results described in the chapter. A separate appendix is devoted to the conversion of S-Plus objects to R objects. In addition, each chapter ends with a set of problems that test readers' grasp of key concepts and techniques and also prepares them for more advanced topics. This book is recommended as a textbook for undergraduate and graduate courses in nonparametric regression. Only a basic knowledge of linear algebra and statistics is required. In addition, this is an excellent resource for researchers and engineers in such fields as pattern recognition, speech understanding, and data mining. Practitioners who rely on nonparametric regression for analyzing data in the physical, biological, and social sciences, as well as in finance and economics, will find this an unparalleled resource.
Download or read book Mathematical Reviews written by and published by . This book was released on 2006 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonparametric Regression Estimates with Censored Data by : Haesook Kim O'Grady
Download or read book Nonparametric Regression Estimates with Censored Data written by Haesook Kim O'Grady and published by . This book was released on 1994 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan
Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Book Synopsis What Does Optimal Bandwidth Selection Mean for Nonparametric Regression Estimation? by : James Stephen Marron
Download or read book What Does Optimal Bandwidth Selection Mean for Nonparametric Regression Estimation? written by James Stephen Marron and published by . This book was released on 1986 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multiple and Generalized Nonparametric Regression by : John Fox
Download or read book Multiple and Generalized Nonparametric Regression written by John Fox and published by SAGE. This book was released on 2000-05 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume introduces this useful technique which makes minimal assumptions about the form of relationship between the average response and the predictors.
