Goodness-Of-Fit Test for Nonparametric Regression Models: Smoothing Spline ANOVA Models as Example [0.03%]
非参数回归模型的拟合优度检验——以平滑样条ANOV模型为例
Sebastian J Teran Hidalgo,Michael C Wu,Stephanie M Engel et al.
Sebastian J Teran Hidalgo et al.
Nonparametric regression models do not require the specification of the functional form between the outcome and the covariates. Despite their popularity, the amount of diagnostic statistics, in comparison to their parametric counter-parts, ...
A joint design for functional data with application to scheduling ultrasound scans [0.03%]
一种功能数据的联合设计及其在超声波扫描调度中的应用
So Young Park,Luo Xiao,Jayson D Willbur et al.
So Young Park et al.
A joint design for sampling functional data is proposed to achieve optimal prediction of both functional data and a scalar outcome. The motivating application is fetal growth, where the objective is to determine the optimal times to collect...
Sheila Gaynor,Eric Bair
Sheila Gaynor
Cluster analysis methods are used to identify homogeneous subgroups in a data set. In biomedical applications, one frequently applies cluster analysis in order to identify biologically interesting subgroups. In particular, one may wish to i...
Analyzing survival curves at a fixed point in time for paired and clustered right-censored data [0.03%]
成对和聚类右删失数据的固定时间点上的生存曲线分析
Pei-Fang Su,Yunchan Chi,Chun-Yi Lee et al.
Pei-Fang Su et al.
In clinical trials, information about certain time points may be of interest in making decisions about treatment effectiveness. Rather than comparing entire survival curves, researchers can focus on the comparison at fixed time points that ...
Feipeng Zhang,Qunhua Li
Feipeng Zhang
Expectile regression is a useful tool for exploring the relation between the response and the explanatory variables beyond the conditional mean. A continuous threshold expectile regression is developed for modeling data in which the effect ...
ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models [0.03%]
线性模型协方差矩阵的ARMA_CHOLESKY因子模型
Keunbaik Lee,Changryong Baek,Michael J Daniels
Keunbaik Lee
In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance...
Samuel M Gross,Robert Tibshirani
Samuel M Gross
A model is presented for the supervised learning problem where the observations come from a fixed number of pre-specified groups, and the regression coefficients may vary sparsely between groups. The model spans the continuum between indivi...
Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study [0.03%]
一种多元函数型响应回归方法及其在宫颈癌前筛查中的应用
Hongxiao Zhu,Jeffrey S Morris,Fengrong Wei et al.
Hongxiao Zhu et al.
Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific pro...
Bayesian variable selection for a semi-competing risks model with three hazard functions [0.03%]
具有三个风险函数的半竞争风险模型的贝叶斯变量选择方法研究
Andrew G Chapple,Marina Vannucci,Peter F Thall et al.
Andrew G Chapple et al.
A variable selection procedure is developed for a semi-competing risks regression model with three hazard functions that uses spike-and-slab priors and stochastic search variable selection algorithms for posterior inference. A rule is devis...
Model-based clustering for assessing the prognostic value of imaging biomarkers and mixed type tests [0.03%]
基于模型的聚类评估影像生物标志物和混合型试验的预后价值
Zheyu Wang,Krisztian Sebestyen,Sarah E Monsell
Zheyu Wang
A model-based clustering method is proposed to address two research aims in Alzheimer's disease (AD): to evaluate the accuracy of imaging biomarkers in AD prognosis, and to integrate biomarker information and standard clinical test results ...