Orthonormal series estimators /, Pons, Odile,

Автор: Saleh
Название: Theory of Ridge Regression Estimators with Applica tions
ISBN: 1118644611 ISBN-13(EAN): 9781118644614
Издательство: Wiley
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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: Arup Bose; Snigdhansu Chatterjee
Название: U-Statistics, Mm-Estimators and Resampling
ISBN: 9811347565 ISBN-13(EAN): 9789811347566
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions. It covers the basics of U-statistics and Mm-estimators and develops their asymptotic properties. 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: Bose
Название: U-Statistics, Mm-Estimators and Resampling
ISBN: 9811322473 ISBN-13(EAN): 9789811322471
Издательство: Springer
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Цена: 8384.00 р.
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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
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Цена: 13275.00 р.
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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: 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
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Цена: 17609.00 р.
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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.