Robust dimension reduction based on canonical correlation
The canonical correlation (CANCOR) method for dimension reduction in a regression setting is based on the classical estimates of the first and second moments of the data, and therefore sensitive to outliers.
Zhou, Jianhui
core
Estimation of multiple networks with common structures in heterogeneous subgroups. [PDF]
J Multivar AnalQin X, Hu J, Ma S, Wu M.
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Testing the equality of error distributions from k independent GARCH models
In this paper we study the problem of testing the null hypothesis that errors from k independent parametrically specified generalized autoregressive conditional heteroskedasticity (GARCH) models have the same distribution versus a general alternative ...
Chandra, S. Ajay
core
Structure Identification, Estimation and Variable Selection for Varying Coefficient EV Models With Longitudinal Data. [PDF]
Stat MedZhao M +5 more
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Nonlinear sufficient dimension reduction for distribution-on-distribution regression. [PDF]
J Multivar AnalZhang Q, Li B, Xue L.
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Nonparametric estimation of multivariate scale mixtures of uniform densities. [PDF]
J Multivar Anal, 2012 Pavlides MG, Wellner JA.
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A Two-Stage Approach for Semilinear In-Slide Models. [PDF]
J Multivar Anal, 2008 You J, Zhou H.
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Marginal models with individual-specific effects for the analysis of longitudinal bipartite networks. [PDF]
Adv Data Anal ClassifBartolucci F, Mira A, Peluso S.
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Explaining Racial Disparities in Amputation Rates for the Treatment of Peripheral Artery Disease (PAD) Using Decomposition Methods. [PDF]
J Racial Ethn Health Disparities, 2017 Mustapha JA +7 more
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HIGH DIMENSIONAL CENSORED QUANTILE REGRESSION. [PDF]
Ann Stat, 2018 Zheng Q, Peng L, He X.
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