about
Statistical Learning Methods for Longitudinal High-dimensional DataRegularization method for predicting an ordinal response using longitudinal high-dimensional genomic data.Penalized nonlinear mixed effects model to identify biomarkers that predict disease progression.A Penalized Likelihood Method for Structural Equation Modeling.Model selection in multivariate semiparametric regression.The impact of repeated organophosphorus pesticide exposure on biomarkers and neurobehavioral outcomes among adolescent pesticide applicators.Hierarchical vector auto-regressive models and their applications to multi-subject effective connectivity.Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies.Variance Component Selection With Applications to Microbiome Taxonomic Data.
P2860
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P2860
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
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2012年學術文章
@zh-hant
name
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS
@en
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS.
@nl
type
label
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS
@en
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS.
@nl
prefLabel
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS
@en
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS.
@nl
P2860
P356
P1433
P1476
VARIABLE SELECTION IN LINEAR MIXED EFFECTS MODELS
@en
P2093
Yingying Fan
P2860
P304
P356
10.1214/12-AOS1028
P50
P577
2012-08-01T00:00:00Z