Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Автор: Borislav D. Bojanov; H. Hakopian; B. Sahakian Название: Spline Functions and Multivariate Interpolations ISBN: 9048142598 ISBN-13(EAN): 9789048142590 Издательство: Springer Рейтинг: Цена: 21655.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spline functions entered Approximation Theory as solutions of natural extremal problems. The emphasis is given to some new developments, such as the general Birkoff`s type interpolation, the extremal properties of the splines and their prominant role in the optimal recovery of functions, multivariate interpolation by polynomials and splines.
Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.
Автор: SCHEMPP; ZELLER Название: Multivariate Approximation Theory III ISBN: 3034899955 ISBN-13(EAN): 9783034899956 Издательство: Springer Рейтинг: Цена: 11173.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics treated cover different problems on multivariate approximation such as polynomial approximation on simplices, multivariate splines (box-splines, dimension of spline spaces), blending methods, multivariate Hermite interpolation, data smoothing and surface representation, and multivariate summation methods.
Автор: Cox Название: An Introduction to Multivariate Data ISBN: 0470689188 ISBN-13(EAN): 9780470689189 Издательство: Wiley Рейтинг: Цена: 5536.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A comprehensive overview of multivariate data and analysis
Providing an introduction to the subject of multivariate data analysis without delving deeply into underlying theory and concepts, An Introduction to Multivariate Data is an excellent resource for undergraduate statistics courses as well as for professionals who require an understanding of statistical techniques for analyzing their own data sets. Focused on real-world application, the book includes sample exercises in each chapter to firmly cement the concepts covered. Exercises range from simple problems that can be solved by hand or with a calculator, while others require the use of computer-based statistical software.
Название: Multivariate Calculus and Geometry ISBN: 1447164180 ISBN-13(EAN): 9781447164180 Издательство: Springer Рейтинг: Цена: 4890.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers multivariate calculus with a combination of geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. It features many practical examples involving problems of several variables.
Описание: Presenting system dynamics as a powerful approach to build simulation models of social systems to aid decision making, this book is grounded in the feedback perspective of complex systems and introduces key concepts such as stocks, flows and feedback. The R programming language provides an open-source and interoperable way to build models.
Автор: Manfred Reimer Название: Multivariate Polynomial Approximation ISBN: 3034894368 ISBN-13(EAN): 9783034894364 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces general theory by presenting the most important facts on multivariate interpolation, quadrature, orthogonal projections and their summation, all treated under a constructive view, and embedded in the theory of positive linear operators.
Автор: Neil H. Timm Название: Applied Multivariate Analysis ISBN: 1441929630 ISBN-13(EAN): 9781441929631 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.
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