Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning

By Alan J. Izenman. 2008

702 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7293d7440d89fc038d7e9ee8d1460cc9b3759478

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Citations in the corpus

Modeling heterogeneous treatment effects in large-scale experiments using Bayesian Additive Regression Trees (2010, methodology): “The number of possible splits for a continuous variable is the number of its unique values −1; the number of possible splits for a nominal variable is 2 M−1 − 1, where M is the number of categories (Izenman 2008).”
Robust Kalman filtering based on Mahalanobis distance as outlier judging criterion (2014, unknown): “Actually the test statistic or the judging index is just the square of the Mahalanobis distance from observation yk to its mean ŷ−k (Izenman 2008, p 60), i.e., γk = M2k = (√( yk − ŷ−k )T ( Pŷ−k )−1 ( yk − ŷ−k ) )2 = (yk − ŷ−k )T ( Pŷ−k )−1 ( yk − ŷ−k ) (11) where Mk = √ (yk − ŷ−k )T(Pŷ−k…”
Optimal selection of reduced rank estimators of high-dimensional matrices (2010, background): “We refer to Chapter 6 in Izenman (2008) for a historical account of the latter.”
A survey of functional principal component analysis (2014, unknown): “61 - 63 for its proof ) .”
mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models (2016, unknown): “…------------------------------------------------------- 1 2 3 0.000004814927 0.000003097694 0.000188461484 2 The Hidalgo stamp data is available at the home page for the book by Izenman (2008) at http://astro.temple. edu/~alan/MMST/datasets.html , or through the package MMST .”
A data-driven statistical model for predicting the critical temperature of a superconductor (2018, background): “Hastie et al. (2009) and Izenman (2008) give general overviews on boosting as well.”