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Reduced Rank Regression, Heinz Schmidli


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Автор: Heinz Schmidli
Название:  Reduced Rank Regression
ISBN: 9783790808711
Издательство: Springer
Классификация:
ISBN-10: 3790808717
Обложка/Формат: Hardcover
Страницы: 179
Вес: 0.34 кг.
Дата издания: 27.07.1995
Серия: Contributions to Statistics
Язык: English
Размер: 254 x 178 x 10
Основная тема: Mathematics
Подзаголовок: With Applications to Quantitative Structure-Activity Relationships
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Reduced rank regression is widely used in statistics to model multivariate data. In this monograph, theoretical and data analytical approaches are developed for the application of reduced rank regression in multivariate prediction problems. Both classical and Bayesian inference are discussed.


Adaptive Systems with Reduced Models

Автор: Petros A. Ioannou; Petar V. Kokotovic
Название: Adaptive Systems with Reduced Models
ISBN: 3540121501 ISBN-13(EAN): 9783540121503
Издательство: Springer
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Цена: 12157.00 р.
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Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations

Автор: Micka?l D. Chekroun; Honghu Liu; Shouhong Wang
Название: Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations
ISBN: 3319125192 ISBN-13(EAN): 9783319125190
Издательство: Springer
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Цена: 6986.00 р.
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Описание: In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs).

Robust Rank-Based and Nonparametric Methods

Автор: Liu
Название: Robust Rank-Based and Nonparametric Methods
ISBN: 3319390635 ISBN-13(EAN): 9783319390635
Издательство: Springer
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Цена: 15372.00 р.
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Описание: The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

Rank-Deficient and Discrete Ill-Posed Problems

Автор: Hansen
Название: Rank-Deficient and Discrete Ill-Posed Problems
ISBN: 0898714036 ISBN-13(EAN): 9780898714036
Издательство: Mare Nostrum (Eurospan)
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Цена: 10659.00 р.
Наличие на складе: Нет в наличии.

Описание: Here is an overview of modern computational stabilization methods for linear inversion, with applications to a variety of problems in audio processing, medical imaging, seismology, astronomy, and other areas. Rank-deficient problems involve matrices that are exactly or nearly rank deficient. Such problems often arise in connection with noise suppression and other problems where the goal is to suppress unwanted disturbances of given measurements. Discrete ill-posed problems arise in connection with the numerical treatment of inverse problems, where one typically wants to compute information about interior properties using exterior measurements. Examples of inverse problems are image restoration and tomography, where one needs to improve blurred images or reconstruct pictures from raw data. This book describes new and existing numerical methods for the analysis and solution of rank-deficient and discrete ill-posed problems. The emphasis is on insight into the stabilizing properties of the algorithms and the efficiency and reliability of the computations.

Harmonic analysis on symmetric spaces-higher rank spaces, positive definite matrix space and generalizations

Автор: Terras, Audrey
Название: Harmonic analysis on symmetric spaces-higher rank spaces, positive definite matrix space and generalizations
ISBN: 1493934066 ISBN-13(EAN): 9781493934065
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This text is an introduction to harmonic analysis on symmetric spaces, focusing on advanced topics such as higher rank spaces, positive definite matrix space and generalizations.

Non-Standard Rank Tests

Автор: Arnold Janssen; David M. Mason
Название: Non-Standard Rank Tests
ISBN: 0387974849 ISBN-13(EAN): 9780387974842
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This monograph extends the notion of locally most powerful rank tests to non-regular cases. An appendix derives the limit experiments needed to investigate the asymptotic optimality of these "non-standard" rank tests under local alternatives.

Handling Missing Data in Ranked Set Sampling

Автор: Carlos N. Bouza-Herrera
Название: Handling Missing Data in Ranked Set Sampling
ISBN: 3642398987 ISBN-13(EAN): 9783642398988
Издательство: Springer
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Цена: 6986.00 р.
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Описание: ГЇВїВЅ The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. Traditionally, simple random sampling is used to select samples. RSS models are developed as counterparts of well-known simple random sampling (SRS) models.

Probability Models and Statistical Analyses for Ranking Data

Автор: Michael A. Fligner; Joseph S. Verducci
Название: Probability Models and Statistical Analyses for Ranking Data
ISBN: 0387979204 ISBN-13(EAN): 9780387979205
Издательство: Springer
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Цена: 16769.00 р.
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Описание: In June of 1990, a conference was held on Probablity Models and Statisti- cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians.

Metric Methods for Analyzing Partially Ranked Data

Автор: Douglas E. Critchlow
Название: Metric Methods for Analyzing Partially Ranked Data
ISBN: 0387962883 ISBN-13(EAN): 9780387962887
Издательство: Springer
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Цена: 19564.00 р.
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Описание: A full ranking of n items is simply an ordering of all these items, of the form: first choice, second choice, *. The problem thus becomes one of ex- tending metrics on the permutation group to metrics on a coset space of the permutation group.

Statistical Methods for Ranking Data

Автор: Mayer Alvo; Philip L.H. Yu
Название: Statistical Methods for Ranking Data
ISBN: 1493947818 ISBN-13(EAN): 9781493947812
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data.

Statistical Methods for Ranking Data

Автор: Mayer Alvo; Philip L.H. Yu
Название: Statistical Methods for Ranking Data
ISBN: 1493914707 ISBN-13(EAN): 9781493914708
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data.

Ranking Of Multivariate Populations

Автор: Corain
Название: Ranking Of Multivariate Populations
ISBN: 1466505540 ISBN-13(EAN): 9781466505544
Издательство: Taylor&Francis
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Цена: 24499.00 р.
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Описание:

Ranking of Multivariate Populations: A Permutation Approach with Applications presents a novel permutation-based nonparametric approach for ranking several multivariate populations. Using data collected from both experimental and observation studies, it covers some of the most useful designs widely applied in research and industry investigations, such as multivariate analysis of variance (MANOVA) and multivariate randomized complete block (MRCB) designs.

The first section of the book introduces the topic of ranking multivariate populations by presenting the main theoretical ideas and an in-depth literature review. The second section discusses a large number of real case studies from four specific research areas: new product development in industry, perceived quality of the indoor environment, customer satisfaction, and cytological and histological analysis by image processing. A web-based nonparametric combination global ranking software is also described.

Designed for practitioners and postgraduate students in statistics and the applied sciences, this application-oriented book offers a practical guide to the reliable global ranking of multivariate items, such as products, processes, and services, in terms of the performance of all investigated products/prototypes.


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