Compared with the conditional mean regression-based scalar-on-function regression model, the scalar-on-function quantile regression is robust to outliers in the response variable. However, it is susceptible to outliers in the functional predictor (called leverage points). This is because the influence...
This article introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance...
We propose a novel and robust online function-on-scalar regression technique via geometric median to learn associations between functional responses and sc
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...
The quantile regression function gives the quantile in the conditional distribution of a response variable given the value of a covariate. It can be used t... DJY Koo - 《Computational Statistics & Data Analysis》 被引量: 85发表: 2000年 Control Charts for Quantile Function Values A control ch...
t-distributionModelling functional data in the presence of spatial dependence is of great practical importance as exemplified by applications in the fields of demography, economy and geography, and has received much attention recently. However, for the classical scalar-on-function regression (SoFR) ...
Extracting information from functional connectivity maps via function-on-scalar regression. NeuroImage 56 (1), 140-148.Reiss P T,Mennes M,Petkova E,et al.Extracting information from functional connectivity maps via function-on-scalar regression. Neuro-Image . 2011...
: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
We propose to: (1) estimate functional regression coefficients using weighted score equations; and (2) perform inference using novel functional balanced repeated replication and survey‐weighted bootstrap for multistage survey designs. This is the first frequentist study to discuss the estimation of ...
In this contribution, the kernel smoothing of the Relative Error Regression (RE-regression) is used to resolve this problem. Precisely, we use the relative square error to establish an estimator of the Hilbertian regression. As asymptotic results, the Hilbertian observations are assumed to be ...