Robust regression and outlier detection book

Robust regression and outlier detection by Annick M. Leroy, Peter J. Rousseeuw

Robust regression and outlier detection Annick M. Leroy, Peter J. Rousseeuw ebook
Publisher: Wiley
Page: 347
ISBN: 0471852333, 9780471852339
Format: pdf

Robust Regression and Outlier Detection by Peter J. Regression analysis identified outliers. Another solution to mitigate these problems is to preprocess the data with an outlier detection algorithm that attempts either to remove outliers altogether or de-emphasize them by giving them less weight than other points when constructing the linear regression model. Robust regression is an alternative to least squares regression when data is contaminated with outliers or influential observations and it can also be used for the purpose of detecting influential observations. About robust regression, robust estimators and statistical procedures, outlier detection, extreme value theory, data cleaning, outlier detection in high dimensional data, non parametric statistics. An even more outlier robust linear regression technique is least median of squares, which is only concerned with the median error made on the training data, not each and every error. WILEY–INTERSCIENCE PAPERBACK SERIES The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. Jeuken J, Sijben A, Alenda C, Rijntjes J, Dekkers M, Boots-Sprenger S, McLendon R, Wesseling P: Robust detection of EGFR copy number changes and EGFR variant III: Technical aspects and relevance for glioma diagnostics. 3 The initial level of income per capita is a robust and significant variable for growth (in terms of conditional or beta convergence). Leroy · Tweetear Book Details: Book Title: Robust Regression and Outlier Detection Author: Peter J. Outlier identification was performed with regression analysis to detect data points at or beyond 95% confidence intervals for residuals. Leroy, “Robust regression and outlier detection”, John Wiley &.