Function-on-scalar regressionImage analysisMinimax rate of convergenceQuantile regressionReproducing kernel Hilbert spaceThis paper develops a novel spatial quantile function-on-scalar regression model, which studies the conditional spatial distribution of a high-dimensional functional response given scalar ...
scalable inference in functional linear regression with streaming data. (2023) arxiv preprint arxiv:2302.02457 yang, h., baladandayuthapani, v., rao, a.u., morris, j.s.: quantile function on scalar regression analysis for distributional data. j. am. stat. assoc. 115 (529), 90–106 (...
Rao, and J.S. Morris, Quantile function on scalar regression analysis for distributional data, J. Am. Stat. Assoc. Appl. Case Stud. 115 (2020), pp. 90–106. (Open in a new window)PubMed (Open in a new window)Web of Science ®(Open in a new window)Google Scholar...
In this paper, we present methods to model the entire marginal distribution of pixel intensities via the quantile function as functional data, regressed on a set of demographic, clinical, and genetic predictors to investigate their effects of imaging-based cancer heterogeneity. We call this approach...
beta分布的概率密度的matlab代码分布数据标量回归分析中的分位数函数 作者贡献清单表 数据 抽象的 多形胶质母细胞瘤(GBM)是最常见和最具侵害性的癌症,始于大脑。 大多数GBM诊断是通过医学成像(例如磁共振成像(MRI))进行的,其中MRI提供了广泛的高分辨率图像对比度,可作为临床决策或GBM研究中肿瘤进展的指标。 通常起...
, n . Then, we fit a function-on-scalar regression as follows: 13 Machine Learning (2024) 113:2765–2794 2773 p ∑ ̃ i(t) = 0(t) + j(t)xij + i(t), i = 1, … , n. j=1 Observe that this model has functional coefficients depending on t, where 0(t) is the func-...
The Bayesian model has two regression coefficient parameters, {wage:age} and {wage: cons}, and a positive scalar parameter, {sigma2}, representing the variance of the error term. The model sum- mary shows the default priors used for the model parameters: normal(0, 10000) for the ...
Quantile Function on Scalar Regression A ... Search in:This JournalAnywhere Advanced search Journal of the American Statistical AssociationVolume 115, 2020 -Issue 529 Submit an articleJournal homepage 2,487 Views 24 CrossRef citations to date 0...
For tensor response regression, the predictors can be a scalar, vector, matrix, or another tensor. The objective of this paper is to determine what areas of the brain are activated by a set of variables. The response variable in this study is a 3d Diffusion Tensor Image (DTI) for each ...
In the contemporary global landscape, understanding the nexus between financial inclusion and natural resource abundance is crucial, especially for resource-rich nations. This study uses diagnostic tests and method of moments quantile regression to exami