Last edited by Nerisar
Sunday, July 26, 2020 | History

1 edition of Multivariate nonparametric methods with R found in the catalog.

Multivariate nonparametric methods with R

Hannu Oja

Multivariate nonparametric methods with R

an approach based on spatial signs and ranks

by Hannu Oja

  • 214 Want to read
  • 28 Currently reading

Published by Springer in New York, N.Y .
Written in English

    Subjects:
  • Multivariate analysis,
  • R (Computer program language)

  • Edition Notes

    Includes bibliographical references and index.

    StatementHannu Oja
    SeriesLecture notes in statistics -- 199
    ContributionsSpringerLink (Online service)
    The Physical Object
    Paginationxiii, 232 p. :
    Number of Pages232
    ID Numbers
    Open LibraryOL25558406M
    ISBN 101441904670
    ISBN 109781441904683, 9781441904676
    LC Control Number2010924740
    OCLC/WorldCa643107550

      Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance. The book is also an excellent reference for practitioners who apply statistical methods in quantitative finance. I never used one, but you can read about it on Hannu Oja's book: Multivariate Nonparametric Methods with R - An approach based on spatial signs and ranks. That book provides the syntaxis to conduct.

    R. The book only assumes minimal prior knowledge of statistics, providing readers with the tools they need right now to help them understand and interpret their data analyses. This book covers univariate, bivariate, and multivariate statistical methods, as well as some nonparametric tests. Multivariate Statistical Methods in Behavioral Research by R. Darrell Bock; The Geometry of Multivariate Statistics by Thomas D. Wickens; Discriminant Analysis by William R. Klecka; Non Parametric. Introduction to Nonparametric Regression by Kunio Takezawa; Applied Nonparametric Statistical Methods, Third Edition by Peter Sprent Nigel Charles.

    It covers a wide range of topics in classical multivariate analysis and presents some deep theoretical results. … It may serve as 'a general reference for the latest developments in the area.' … In summary, Multivariate Nonparametric Methods With R is a good reference book for the area of multivariate nonparametric methods based on. Designed for researchers and students who wish to apply these models to their own work in a flexible manner. (0 ) pp. Statistical Methods for Forecasting Bovas Abraham and Johannes Ledolter This practical, user-oriented book treats the statistical methods and models used to produce short-term forecasts.


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Multivariate nonparametric methods with R by Hannu Oja Download PDF EPUB FB2

In summary, Multivariate Nonparametric Methods With R is a good reference book for the area of multivariate nonparametric methods based on spatial signs and ranks .”. Multivariate nonparametric methods with R book Shen, Journal of the American Statistical Association, Vol.

(), December, ) “This book provides an overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. .Cited by: The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks.

The classical book by Puri and Sen () uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. In summary, Multivariate Nonparametric Methods With R is a good reference book for the area of multivariate nonparametric methods based on spatial signs and ranks ." (Gang Shen, Journal of the American Statistical Association, Vol.

(), December, )Author: Hannu Oja. BOOK REVIEWS Multivariate Nonparametric Methods with R. An Approach Based on Spatial Signs and Ranks by OJA, : Mia Hubert. In summary, Multivariate Nonparametric Methods With R is a good reference book for the area of multivariate nonparametric methods based on spatial signs and ranks ." (Gang Shen, Journal of the American Statistical Association, Vol.

(), December, ) "This book provides an overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. Multivariate Nonparametric Methods with R: An approach based on spatial signs and ranks (Lecture Notes in Statistics) This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data.

Medical books Multivariate Nonparametric Methods with R. Multivariate Nonparametric Methods with R. An Approach Based on Spatial Signs and Ranks by H. OJA Article (PDF Available) in Biometrics 67(4) December with Reads. In this book nonparametric and robust competitors to standard multivariate inference methods based on (multivariate) spatial signs and ranks are introduced and discussed in detail.

An R statistical Author: Hannu Oja. Multivariate nonparametric methods with R: an approach based on spatial signs and ranks. [Hannu Oja] -- Offers a fresh, fairly efficient, and robust alternative to analyzing multivariate data.

This monograph provides an overview of the theory of multivariate nonparametric methods based. method a character string indicating what type of test was performed. a character string giving the name of the data set. Author(s) Klaus Nordhausen References Oja, H. (), Multivariate Nonparametric Methods with R, Springer.

Nordhausen, K. and Oja, H. (), Multivariate L1 Methods: The Package MNM, Journal of. brief account of many of the modern topics in nonparametric inference. The book is aimed at master’s-level or Ph.D.-level statistics and computer science students. It is also suitable for researchers in statistics, machine learn-ing and data mining who want to get up to speed quickly on modern non-parametric methods.

In this book we describe procedures called nonparametric and distribution-free methods. Nonparametric methods provide an alternative series of statistical methods that require no.

Multivariate nonparametric methods with R: an approach based on spatial signs and ranks. [Hannu Oja] Book, Internet Resource: All Authors / Contributors: Hannu Oja.

Find more information about: ISBN: OCLC Number: Description. The book will be refered to as the MNM book. Author(s) Klaus Nordhausen, Jyrki Mttnen and Hannu Oja Maintainer: Klaus Nordhausen, [email protected] References.

Oja, H. (), Multivariate Nonparametric Methods with R. Nonparametric Statistical Methods Using R covers traditional nonparamet-ric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses.

The authors emphasize ap - plications and statistical computation. Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance.

The book is also an excellent reference for practitioners who apply statistical methods in quantitative by: 3. Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science. Author(s): Daniel J. Denis; First published: 27 March Print ISBN: | Online ISBN: | DOI: / About this book.

The book provides coverage of key statistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, and nearest neighbor methods. Exploring the additional applications of nonparametric and semiparametric methods, Multivariate Nonparametric Regression and Visualization features.

Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance.

The book is also an excellent reference for practitioners who apply statistical methods in quantitative : $ Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods.

The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for. Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models.

It follows the approach of the first edition by developing rank.Multivariate nonparametric statistical tests of hypotheses are described for the one-sample location problem, the several-sample location problem and the problem of testing independence between.

Jussi Klemelä, PhD, is Adjunct Professor at the University of Oulu. His research interests include nonparametric function estimation, density estimation, and data visualization. He is the author of Smoothing of Multivariate Data: Density Estimation and Visualization and Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance.