quantile regressionThis paper studies estimation in functional linear quantile regression in which the dependent variable is scalar while the covariate is a function, and the conditional quantile for each fixed quantile index is modeled as a linear functional of the covariate. Here we sup...
In this paper, we consider the estimation and inference in partially functional linear regression with multiple functional covariates. We estimate the parameters and the slope functions by using functionalprincipal component analysis(FPCA) approach to each functional covariate; establish theasymptotic distrib...
Partially functional linear quantile regression model and variable selection with censoring indicators MAR Journal of Multivariate Analysis Volume 197,September 2023, Page 105189 Purchase options CorporateFor R&D professionals working in corporate organizations. ...
L1-norm approach is used to construct the local linear estimator of the spatial regression quantile for functional regressors. Under mixing spatial condition, we establish the almost complete convergence of the constructed approach. The applicability of the constructed estimator is examined by a Monte-...
The estimates of the parameter functions for each quantile regression model are obtained based on the entire data set, not the observations in the given quantile level. Therefore, the estimation phase of the quantile parameters is computationally intensive and requires the use of linear programming ...
Function-on-Function Partial Quantile Regression Article 27 September 2021 Explore related subjects Discover the latest articles and news from researchers in related subjects, suggested using machine learning. Econometrics Functional clustering Linear Models and Regression Non-parametric Inference Statisti...
Linear regression was performed to determine the correlation between the two methods and Bland-Altman plots were generated83,106. Maximum Cg.Th determined by the two techniques was strongly correlated (R2 = 0.91, MTP, P < 0.0001, R2 = 0.755, LTP, P < 0.0001, Supplementary...
acuminata and water depth zones using quantile regression analysis, linear regression analysis and one-way ANOVA. One-way ANCOVA was used to evaluate the effects of water depth (factor) on the relationships between root, stem and leaf mass, leaf area, specific leaf area, root-shoot ratio and ...
(P) values on the y-axis. Linear regression models were adjusted for age, age2, sex, age × sex, age2 × sex, head motion from resting-state fMRI, head position, volumetric scaling factor needed to normalize for head size, genotyping array and 10 genetic principal components. ...
Rios-Avila, F., Maroto, M.L.: Moving beyond linear regression: implementing and interpreting quantile regression models with fixed effects. Sociol Methods Res. 004912412110361. (2022). https://doi.org/10.1177/00491241211036165 Savage, M., Devine, F., Cunningham, N., Taylor, M., Li, Y., ...