Estimands, estimators and sensitivity analysis in clinical trials, Mallinckrodt, Craig Molenberghs, Geert Lipkovich, Ilya (quintiles, Durham, North Carolina, Usa) Ratitch, Bohdana (eli Lilly Cananda, Ontario, Canada)
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: Arup Bose; Snigdhansu Chatterjee Название: U-Statistics, Mm-Estimators and Resampling ISBN: 9811347565 ISBN-13(EAN): 9789811347566 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Поставка под заказ.
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: 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: 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: 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.
Описание: For a chemist who is concerned with the synthesis of new energetic compounds, it is essential to be able to assess physical and thermodynamic properties, as well as the sensitivity, of possible new energetic compounds before synthesis is attempted. Various approaches have been developed to predict important aspects of the physical and thermodynamic properties of energetic materials including (but not limited to): crystal density, heat of formation, melting point, enthalpy of fusion and enthalpy of sublimation of an organic energetic compound. Since an organic energetic material consists of metastable molecules capable of undergoing very rapid and highly exothermic reactions, many methods have been developed to estimate the sensitivity of an energetic compound with respect to detonationcausing external stimuli such as heat, friction, impact, shock and electrostatic discharge. This book introduces these methods and demonstrates those methods which can be easily applied.
Автор: David Rios Insua Название: Sensitivity Analysis in Multi-objective Decision Making ISBN: 3540526927 ISBN-13(EAN): 9783540526926 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text introduces a general framework for sensitivity analysis in multi-objective decision making. A theory of decision making, new sensitivity tools based on gauge functions and Bayesian hypothesis testing, and a description of their implementation are included.
Автор: Garban Название: Noise Sensitivity of Boolean Functions and Percolation ISBN: 1107432553 ISBN-13(EAN): 9781107432550 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This account of the new and exciting area of noise sensitivity of Boolean functions - in particular applied to critical percolation - is designed for graduate students and researchers in probability theory, discrete mathematics, and theoretical computer science. It assumes a basic background in probability theory and integration theory. Each chapter ends with exercises.
Автор: Emmanuel Laporte; Patrick Le Tallec Название: Numerical Methods in Sensitivity Analysis and Shape Optimization ISBN: 1461265983 ISBN-13(EAN): 9781461265986 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Numerical Methods in Sensitivity Analysis and Shape Optimization will be of interest to graduate students involved in mathematical modeling and simulation, as well as engineers and researchers in applied mathematics looking for an up-to-date introduction to optimization techniques, sensitivity analysis, and optimal design.
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