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Lasso penalized model selection criteria for high-dimensional multivariate linear regression analysis
Katayama, Shota; Imori, Shinpei - In: Journal of Multivariate Analysis 132 (2014) C, pp. 138-150
selection consistency, that is, they can asymptotically pick out the true model. Simulation studies show that the proposed …
Persistent link: https://www.econbiz.de/10010939517
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Consistency of sparse PCA in High Dimension, Low Sample Size contexts
Shen, Dan; Shen, Haipeng; Marron, J.S. - In: Journal of Multivariate Analysis 115 (2013) C, pp. 317-333
model and assume in addition that the maximal eigenvector is sparse. We extend the existing HDLSS asymptotic consistency and … under which sparse PCA is still consistent even when conventional PCA is strongly inconsistent. The consistency of sparse … sparse PCA consistency, by showing strong inconsistency for an oracle version of sparse PCA beyond the consistent region, as …
Persistent link: https://www.econbiz.de/10010608101
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Variable selection for general transformation models with right censored data via nonconcave penalties
Li, Jianbo; Gu, Minggao; Zhang, Riquan - In: Journal of Multivariate Analysis 115 (2013) C, pp. 445-456
In this paper, we consider variable selection for general transformation models with right censored data via nonconcave penalties. We will conduct the variable selection by maximizing the penalized log-marginal likelihood function. In the proposed variable selection procedures, we not only can...
Persistent link: https://www.econbiz.de/10010608106
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A Conditional Test for a Non-negative Mean Vector Based on a Hotelling'sT2-Type Statistic
Wang, Yining; McDermott, Michael P. - In: Journal of Multivariate Analysis 66 (1998) 1, pp. 64-70
. The consistency and invariance of the new test are also established …
Persistent link: https://www.econbiz.de/10005006607
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On Marginal Quasi-Likelihood Inference in Generalized Linear Mixed Models
Sutradhar, Brajendra C.; Rao, R. Prabhakar - In: Journal of Multivariate Analysis 76 (2001) 1, pp. 1-34
In view of the cumbersome and often intractable numerical integrations required for a full likelihood analysis, several suggestions have been made recently for approximate inference in generalized linear mixed models (GLMMs). Two closely related approximate methods are the penalized...
Persistent link: https://www.econbiz.de/10005160323
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On the consistency of coordinate-independent sparse estimation with BIC
Zou, Changliang; Chen, Xin - In: Journal of Multivariate Analysis 112 (2012) C, pp. 248-255
Chen et al. (2010) [1] propose a unified method–coordinate-independent sparse estimation (CISE)–that is able to simultaneously achieve sparse sufficient dimension reduction and screen out irrelevant and redundant variables efficiently. However, its attractive features depend on the...
Persistent link: https://www.econbiz.de/10010594232
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Frontier estimation with kernel regression on high order moments
Girard, Stéphane; Guillou, Armelle; Stupfler, Gilles - In: Journal of Multivariate Analysis 116 (2013) C, pp. 172-189
goes to zero. The consistency of the estimator is proved under mild conditions on these two parameters. The asymptotic …
Persistent link: https://www.econbiz.de/10010665700
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Direct variable selection for discrimination among several groups
Nkiet, Guy Martial - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 151-163
We propose a criterion for variable selection in discriminant analysis. This criterion permits to arrange the variables in decreasing order of adequacy for discrimination, so that the variable selection problem reduces to that of the estimation of suitable permutation and dimensionality. Then,...
Persistent link: https://www.econbiz.de/10010572276
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Error covariance matrix correction based approach to functional coefficient regression models with generated covariates
Li, XiaoLi; You, JinHong - In: Journal of Multivariate Analysis 107 (2012) C, pp. 263-281
In this paper, we are concerned with the estimating problem of functional coefficient regression models with generated covariates. A new local polynomial estimation is proposed, which is based on error covariance matrix correction. It is shown that the resulting estimators are consistent,...
Persistent link: https://www.econbiz.de/10010572293
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Nonparametric estimation of multivariate scale mixtures of uniform densities
Pavlides, Marios G.; Wellner, Jon A. - In: Journal of Multivariate Analysis 107 (2012) C, pp. 71-89
characterizations, and prove strong consistency of the almost surely unique maximum likelihood estimator (MLE) in FSMU(d). We also …(d). We study maximum likelihood estimation in the family FSMU(d). We prove existence of the MLE, establish Fenchel … global and local rates of convergence of the MLE. …
Persistent link: https://www.econbiz.de/10011041983