Statistical Theory and Computational Aspects of Smoothing (Paperback)

Michael Schimek

ISBN 10: 3790809306 / ISBN 13: 9783790809305

Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 1996

About this Item

Paperback. One of the main applications of statistical smoothing techniques is non-parametric regression. For the last 15 years there has been a strong theoretical interest in the development of such techniques. Related algorithmic concepts have been a main concern in computational statistics. Smoothing techniques in regression, as well as other statistical methods are increasingly applied in biosciences and economics. But they are also relevant for medical and psychological research. This proceedings volume introduces new developments in scatterplot smoothing and applications in statistical modelling. The treatment of the topics is on an intermediate level avoiding too many technicalities. Computational and applied aspects are considered throughout. Of particular interest to readers is the discussion of recent local fitting techniques. One of the main applications of statistical smoothing techniques is nonparametric regression. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. Introduced are new developments in scatterplot smoothing and applications in statistical modelling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783790809305

Bibliographic Details

• Title: Statistical Theory and Computational Aspects of Smoothing (Paperback)
• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg
• Publication Date: 1996
• Language: English
• ISBN 10: 3790809306
• ISBN 13: 9783790809305
• Binding: Paperback
• Condition: new

About this title

Synopsis

One of the main applications of statistical smoothing techniques is nonparametric regression. For the last 15 years there has been a strong theoretical interest in the development of such techniques. Related algorithmic concepts have been a main concern in computational statistics. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. But they are also relevant for medical and psychological research. Introduced are new developments in scatterplot smoothing and applications in statistical modelling. The treatment of the topics is on an intermediate level avoiding too much technicalities. Computational and applied aspects are considered throughout. Of particular interest to readers is the discussion of recent local fitting techniques.