Описание: Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote.
Автор: Good Phillip I Название: Introduction to Statistics Through Resampling Methods and R ISBN: 1118428218 ISBN-13(EAN): 9781118428214 Издательство: Wiley Рейтинг: Цена: 8862.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see... it would make a good nightstand book for every statistician.
Описание: "Peter [Bruce] has provided relevant, newsworthy and interesting examples, and, he has the reader doing all sorts of experiments ... for getting the feel of the statistical process. I believe the topics cover the waterfront of what a primer should consist of. " From a User at Statistics.
Автор: Pons, Odile, Название: Orthonormal series estimators / ISBN: 9811210683 ISBN-13(EAN): 9789811210686 Издательство: World Scientific Publishing Рейтинг: Цена: 14256.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The approximation and the estimation of nonparametric functions by projections on an orthonormal basis of functions are useful in data analysis. This book presents series estimators defined by projections on bases of functions, they extend the estimators of densities to mixture models, deconvolution and inverse problems, to semi-parametric and nonparametric models for regressions, hazard functions and diffusions. They are estimated in the Hilbert spaces with respect to the distribution function of the regressors and their optimal rates of convergence are proved. Their mean square errors depend on the size of the basis which is consistently estimated by cross-validation. Wavelets estimators are defined and studied in the same models.The choice of the basis, with suitable parametrizations, and their estimation improve the existing methods and leads to applications to a wide class of models. The rates of convergence of the series estimators are the best among all nonparametric estimators with a great improvement in multidimensional models. Original methods are developed for the estimation in deconvolution and inverse problems. The asymptotic properties of test statistics based on the estimators are also established.
Автор: Saleh Название: Theory of Ridge Regression Estimators with Applica tions ISBN: 1118644611 ISBN-13(EAN): 9781118644614 Издательство: Wiley Рейтинг: Цена: 16466.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book discusses current methods of estimation in linearmodels. In particular, the authors address the methodology oflinear multiple regression models that plays an important role inalmost every scientific investigations in various fields, including economics, engineering, and biostatistics. Thestandard estimation method for regression parameters is theordinary least square (OLS) principal where residual squared errorsare minimized. Applied statisticians are often not satisfied withOLS estimators when the design matrix is ill-conditioned, leadingto a multicollinearity problem and large variances that make the"prediction" inaccurate. This book details theridge regression estimator, which was developed to combat themulticollinearity problem. Another estimator, called theLiu-estimator due to Liu Kejian, is also addressed since itprovides a competing resolution to the multicollinearityproblem. The ridge regression estimators are complicatednon-linear functions of the ridge parameter, whereas, theLiu estimators are a linear function of the shrinkage parameter.With a focus on the ridge regression and LIU estimators, this bookprovides expanded coverage beyond the usual preliminary test andStein type estimator. In this case, we propose a class of compositeestimators that are obtained by multiplying the OLS, restrictedOLS, preliminary test OLS, and Stein-type OLS by the "ridgefactor" and "Liu-factor." This research is asignificant step towards the study of dominance properties as wellas the comparison of the extent of LASSO properties. In addition, research materials involving shrinkage and model selection forlinear regression models are provided. Topical coverageincludes: preliminaries; linear regression models; multipleregression models; measurement error models; generalized linearmodels; and autoregressive Gaussian processes.
Автор: Bose Название: U-Statistics, Mm-Estimators and Resampling ISBN: 9811322473 ISBN-13(EAN): 9789811322471 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions. It also provides an elementary introduction to resampling, particularly in the context of these estimators. The last chapter is on practical implementation of the methods presented in other chapters, using the free software R.
Автор: V.G. Voinov; M.S. Nikulin Название: Unbiased Estimators and their Applications ISBN: 0792339398 ISBN-13(EAN): 9780792339397 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains problems of parametric point estimation for multivariate probability distributions emphasizing problems of unbiased estimation. This book covers some basic properties of multivariate continuous and discrete distributions, the general theory of point estimation in multivariate case, and techniques for constructing unbiased estimators.
Автор: S. N. Lahiri Название: Resampling Methods for Dependent Data ISBN: 1441918485 ISBN-13(EAN): 9781441918482 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout.
Автор: Mallinckrodt, Craig Molenberghs, Geert Lipkovich, Ilya (quintiles, Durham, North Carolina, Usa) Ratitch, Bohdana (eli Lilly Cananda, Ontario, Canada) Название: Estimands, estimators and sensitivity analysis in clinical trials ISBN: 1138592501 ISBN-13(EAN): 9781138592506 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will use the new guidance as a framework for developing and implementing comprehensive analysis plans for clinical trials that support the development and approval of medical interventions.
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