<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multivariate on Aayush Bajaj's Augmenting Infrastructure</title><link>https://abaj.ai/tags/multivariate/</link><description>Recent content in Multivariate on Aayush Bajaj's Augmenting Infrastructure</description><generator>Hugo</generator><language>en</language><copyright>© 2026 Aayush Bajaj</copyright><lastBuildDate>Sat, 26 Sep 2026 15:48:48 +1000</lastBuildDate><atom:link href="https://abaj.ai/tags/multivariate/index.xml" rel="self" type="application/rss+xml"/><item><title>Applied Multivariate Statistical Analysis</title><link>https://abaj.ai/words/library/books/applied_multivariate_statistical_analysis_johnson_wichern/</link><pubDate>Sat, 26 Sep 2026 09:00:00 +1000</pubDate><guid>https://abaj.ai/words/library/books/applied_multivariate_statistical_analysis_johnson_wichern/</guid><description>&lt;p>&lt;em>Applied Multivariate Statistical Analysis&lt;/em> (6th edition, Pearson, 2007) by Johnson and Wichern — the classic applied treatment of multivariate methods: the multivariate normal, inference about mean vectors, MANOVA, covariance structure, principal components, factor analysis, canonical correlation, discrimination and classification, and clustering, grounded throughout in worked data examples.&lt;/p></description></item></channel></rss>