Robust Multivariate Analysis (Hardback)David J. Olive (author)
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The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided.
Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author's website.
Publisher: Springer International Publishing AG
Number of pages: 501
Weight: 9927 g
Dimensions: 235 x 155 mm
Edition: 1st ed. 2017
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