Xiaotong Shen,Hsin-Cheng Huang
Xiaotong Shen
Extracting grouping structure or identifying homogenous subgroups of predictors in regression is crucial for high-dimensional data analysis. A low-dimensional structure in particular-grouping, when captured in a regression model, enables to...
Generalized Functional Linear Models with Semiparametric Single-Index Interactions [0.03%]
具有半参单指标交互效应的广义泛函线性模型
Yehua Li,Naisyin Wang,Raymond J Carroll
Yehua Li
We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in th...
Regularization Parameter Selections via Generalized Information Criterion [0.03%]
广义信息准则下的正则化参数选择方法研究
Yiyun Zhang,Runze Li,Chih-Ling Tsai
Yiyun Zhang
We apply the nonconcave penalized likelihood approach to obtain variable selections as well as shrinkage estimators. This approach relies heavily on the choice of regularization parameter, which controls the model complexity. In this paper,...
Hierarchical Spatial Process Models for Multiple Traits in Large Genetic Trials [0.03%]
大规模育种试验中多性状的层次化空间过程模型
Sudipto Banerjee,Andrew O Finley,Patrik Waldmann et al.
Sudipto Banerjee et al.
This article expands upon recent interest in Bayesian hierarchical models in quantitative genetics by developing spatial process models for inference on additive and dominance genetic variance within the context of large spatially reference...
Using DNA fingerprints to infer familial relationships within NHANES III households [0.03%]
利用DNA指纹图谱推断NHANES III家庭中的亲缘关系
Hormuzd A Katki,Christopher L Sanders,Barry I Graubard et al.
Hormuzd A Katki et al.
Developing, targeting, and evaluating genomic strategies for population-based disease prevention require population-based data. In response to this urgent need, genotyping has been conducted within the Third National Health and Nutrition Ex...
Lan Wang,Bo Kai,Runze Li
Lan Wang
By allowing the regression coefficients to change with certain covariates, the class of varying coefficient models offers a flexible approach to modeling nonlinearity and interactions between covariates. This paper proposes a novel estimati...
Ciprian M Crainiceanu,Ana-Maria Staicu,Chong-Zhi Di
Ciprian M Crainiceanu
We introduce Generalized Multilevel Functional Linear Models (GMFLMs), a novel statistical framework for regression models where exposure has a multilevel functional structure. We show that GMFLMs are, in fact, generalized multilevel mixed ...
On Consistency and Sparsity for Principal Components Analysis in High Dimensions [0.03%]
高维主成分分析的稳健性和稀疏性
Iain M Johnstone,Arthur Yu Lu
Iain M Johnstone
Principal components analysis (PCA) is a classic method for the reduction of dimensionality of data in the form of n observations (or cases) of a vector with p variables. Contemporary datasets often have p comparable with or even much large...
S A Murphy,D Bingham
S A Murphy
Dynamic treatment regimes are time-varying treatments that individualize sequences of treatments to the patient. The construction of dynamic treatment regimes is challenging because a patient will be eligible for some treatment components o...