Pratim Guha Niyogi,Ping-Shou Zhong
Pratim Guha Niyogi
We address the challenge of estimation in the context of constant linear effect models with dense functional responses. In this framework, the conditional expectation of the response curve is represented by a linear combination of functiona...
A non-parametric U-statistic testing approach for multi-arm clinical trials with multivariate longitudinal data [0.03%]
多重纵向数据分析下的多臂临床试验的非参数U统计量检验方法研究
Dhrubajyoti Ghosh,Sheng Luo
Dhrubajyoti Ghosh
Randomized clinical trials (RCTs) often involve multiple longitudinal primary outcomes to comprehensively assess treatment efficacy. The Longitudinal Rank-Sum Test (LRST) [17], a robust U-statistics-based, non-parametric, rank-based method,...
Debangan Dey,Sudipto Banerjee,Martin A Lindquist et al.
Debangan Dey et al.
The manuscript considers multivariate functional data analysis with a known graphical model among the functional variables representing their conditional relationships (e.g., brain region-level fMRI data with a prespecified connectivity gra...
From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas [0.03%]
从多元分析到函数数据分析：基础、最新发展和新兴领域
Yehua Li,Yumou Qiu,Yuhang Xu
Yehua Li
Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental ...
Modeling the Cholesky factors of covariance matrices of multivariate longitudinal data [0.03%]
多元纵向数据协方差矩阵的Cholesky分解的建模问题研究
Priya Kohli,Tanya P Garcia,Mohsen Pourahmadi
Priya Kohli
Modeling the covariance matrix of multivariate longitudinal data is more challenging as compared to its univariate counterpart due to the presence of correlations among multiple responses. The modified Cholesky block decomposition reduces t...
Nonlinear sufficient dimension reduction for distribution-on-distribution regression [0.03%]
分布对分布回归的非线性充分降维
Qi Zhang,Bing Li,Lingzhou Xue
Qi Zhang
We introduce a new approach to nonlinear sufficient dimension reduction in cases where both the predictor and the response are distributional data, modeled as members of a metric space. Our key step is to build universal kernels (cc-univers...
Estimation of multiple networks with common structures in heterogeneous subgroups [0.03%]
具有子群共性结构的多网络估计问题研究
Xing Qin,Jianhua Hu,Shuangge Ma et al.
Xing Qin et al.
Network estimation has been a critical component of high-dimensional data analysis and can provide an understanding of the underlying complex dependence structures. Among the existing studies, Gaussian graphical models have been highly popu...
Functional delta residuals and applications to simultaneous confidence bands of moment based statistics [0.03%]
功能德尔塔残差及其在矩统计同时置信带中的应用
Fabian J E Telschow,Samuel Davenport,Armin Schwartzman
Fabian J E Telschow
Given a functional central limit (fCLT) for an estimator and a parameter transformation, we construct random processes, called functional delta residuals, which asymptotically have the same covariance structure as the limit process of the f...
Andrew J Holbrook
Andrew J Holbrook
We present the simplicial sampler, a class of parallel MCMC methods that generate and choose from multiple proposals at each iteration. The algorithm's multiproposal randomly rotates a simplex connected to the current Markov chain state in ...
Jun Li
Jun Li
When sample sizes are small, it becomes challenging for an asymptotic test requiring diverging sample sizes to maintain an accurate Type I error rate. In this paper, we consider one-sample, two-sample and ANOVA tests for mean vectors when d...