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Partially Linear Models, Wolfgang H?rdle; Hua Liang; Jiti Gao


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Автор: Wolfgang H?rdle; Hua Liang; Jiti Gao
Название:  Partially Linear Models
ISBN: 9783790813005
Издательство: Springer
Классификация:



ISBN-10: 3790813001
Обложка/Формат: Paperback
Страницы: 206
Вес: 0.31 кг.
Дата издания: 14.09.2000
Серия: Contributions to Statistics
Язык: English
Размер: 236 x 155 x 14
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics.

An Introduction to Generalized Linear Models, Third Edition

Название: An Introduction to Generalized Linear Models, Third Edition
ISBN: 1584889500 ISBN-13(EAN): 9781584889502
Издательство: Taylor&Francis
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Цена: 47970.00 T
Наличие на складе: Поставка под заказ.
Описание: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.

Regression Analysis and Linear Models: Concepts, Applications, and Implementation

Автор: Darlington Richard B., Hayes Andrew F.
Название: Regression Analysis and Linear Models: Concepts, Applications, and Implementation
ISBN: 1462521134 ISBN-13(EAN): 9781462521135
Издательство: Taylor&Francis
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Цена: 83690.00 T
Наличие на складе: Невозможна поставка.
Описание: Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book`s examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable`s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Linear Mathematical Models In Chemical Engineering

Автор: Martin A Hjortso
Название: Linear Mathematical Models In Chemical Engineering
ISBN: 9812794158 ISBN-13(EAN): 9789812794154
Издательство: World Scientific Publishing
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Цена: 111930.00 T
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Описание: Reviews, introduces, and develops the mathematics that is encountered in sophisticated chemical engineering models. This book provides coverage of chemical engineering model formulation and analysis. It serves as an introduction to linear mathematics for engineering students.

Applied Linear Statistical Models with Student CD

Автор: Nachtsheim;Neter;Kutner
Название: Applied Linear Statistical Models with Student CD
ISBN: 0071122214 ISBN-13(EAN): 9780071122214
Издательство: McGraw-Hill
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Цена: 61770.00 T
Наличие на складе: Поставка под заказ.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

Partially Observable Linear Systems Under Dependent Noises

Автор: Agamirza E. Bashirov
Название: Partially Observable Linear Systems Under Dependent Noises
ISBN: 3034894074 ISBN-13(EAN): 9783034894074
Издательство: Springer
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Цена: 93160.00 T
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Описание:

Noise is a rich concept playing an underlying role in human activity. Consideration of the noise phenomenon in arts and sciences, respectively, makes the distinction between both domains more obvious. Artists create "deliberate noise" ; the masterpieces of literature, music, modern fine art etc. are those where a clear idea, traditionally related to such concepts as love, is presented under a skilful veil of "deliberate noise." On the contrary, sciences fight against noise; a scientific discovery is a law of nature extracted from a noisy medium and refined.

This book discusses the methods of fighting against noise. It can be regarded as a mathematical view of specific engineering problems with known and new methods of control and estimation in noisy media.

The main feature of this book is the investigation of stochastic optimal control and estimation problems with the noise processes acting dependently on the state (or signal) and observation systems. While multiple early and recent findings on the subject have been obtained and challenging problems remain to be solved, this subject has not yet been dealt with systematically nor properly investigated. The discussion is given for infinite dimensional systems, but within the linear quadratic framework for continuous and finite time horizon. In order to make this book self-contained, some background material is provided.

Consequently, the target readers of this book are both applied mathematicians and theoretically oriented engineers who are designing new technology, as well as students of the related branches. The book may also be used as a reference manual in that part of functional analysis that is needed for problems of infinite dimensional linear systems theory.


Partially Integrable Evolution Equations in Physics

Автор: R. Conte; N. Boccara
Название: Partially Integrable Evolution Equations in Physics
ISBN: 9401067546 ISBN-13(EAN): 9789401067546
Издательство: Springer
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Цена: 81050.00 T
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Описание: Proceedings of the NATO Advanced Study Institute on Partially Integrable Nonlinear Evolution Equations and Their Physical Applications, Les Houches, France, March 21-30, 1989

Learning with Partially Labeled and Interdependent Data

Автор: Massih-Reza Amini; Nicolas Usunier
Название: Learning with Partially Labeled and Interdependent Data
ISBN: 331935390X ISBN-13(EAN): 9783319353906
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data.

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
Рейтинг:
Цена: 130430.00 T
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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.

Feedback Strategies for Partially Observable Stochastic Systems

Автор: Y. Yavin
Название: Feedback Strategies for Partially Observable Stochastic Systems
ISBN: 3540122087 ISBN-13(EAN): 9783540122081
Издательство: Springer
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Цена: 81050.00 T
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Semi-algebraic Function Rings and Reflectors of Partially Ordered Rings

Автор: Niels Schwartz; James J. Madden
Название: Semi-algebraic Function Rings and Reflectors of Partially Ordered Rings
ISBN: 3540664602 ISBN-13(EAN): 9783540664604
Издательство: Springer
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Цена: 41880.00 T
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Описание: This text lays algebraic foundations for real geometry through a systematic investigation of partially ordered rings of semi-algebraic functions. It also covers topics such as ordered algebraic structures, topology and rings of continuous functions.

Partially Specified Matrices and Operators: Classification, Completion, Applications

Автор: Israel Gohberg; Marinus Kaashoek; Frederik Van Sch
Название: Partially Specified Matrices and Operators: Classification, Completion, Applications
ISBN: 3034899068 ISBN-13(EAN): 9783034899062
Издательство: Springer
Рейтинг:
Цена: 97820.00 T
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Linear models with R

Автор: Faraway Julian J
Название: Linear models with R
ISBN: 1439887330 ISBN-13(EAN): 9781439887332
Издательство: Taylor&Francis
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Цена: 91860.00 T
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Описание:

A Hands-On Way to Learning Data Analysis

Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.

New to the Second Edition

  • Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality
  • Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates
  • Extensive use of the ggplot2 graphics package in addition to base graphics

Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.



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