We propose a novel and robust online function-on-scalar regression technique via geometric median to learn associations between functional responses and scalar covariates based on massive or streaming datasets. The online estimation procedure, developed using the average stochastic gradient descent algorithm...
They studied an estimation of the volume under an ROC surface using a semiparametric regression model. In this cited work, the local linear approach is used to estimate the nonparametric competence of the location-scale regression models. Ref. [13] considered the local linear estimator of the ...
:exclamation: This is a read-only mirror of the CRAN R package repository. MECfda — Scalar-on-Function Regression with Measurement Error Correction - GitHub - cran/MECfda: :exclamation: This is a read-only mirror of the CRAN R package repository. ME
In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive ...
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...
Li, Y., and Hsing, T. (2010), “Uniform Convergence Rates for Nonparametric Regression and Principal Component Analysis in Functional/Longitudinal Data,”The Annals of Statistics, 38, 3321–3351. DOI: 10.1214/10-AOS813. Web of Science ®Google Scholar ...
Functional regressionOracle propertyApplications of functional data with large numbers of predictors have grown precipitously in recent years, driven, in part, by rapid advances in genotyping technologies. Given the large numbers of genetic mutations encountered in genetic association studies, statistical ...
This paper presents a new methodology, called AFSSEN, to simultaneously select significant predictors and produce smooth estimates in a high-dimensional function-on-scalar linear model with a sub-Gaussian errors. Outcomes are assumed to lie in a general real separable Hilbert space, H, while ...
We propose a novel and robust online function-on-scalar regression technique via geometric median to learn associations between functional responses and sc
functional response regressionglobal-local shrinkageproteomic biomarkerquantile regressionMass spectrometry proteomics, characterized by spiky, spatially heterogeneous functional data, can be used to identify potential cancer biomarkers. Existing mass spectrometry analyses utilize mean regression to detect spectral ...