ArticleJournal of multivariate analysis2022
Inference in Functional Linear Quantile Regression.
Article in Journal of multivariate analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Correcting Measurement Error and Zero Inflation in Functional Covariates for Scalar-on-Function Quantile Regression.Statistics in medicine · 2026Article
- When digital tracking helps or hinders: unpacking the heterogeneous effects of activity trackers on adolescent athletes through the lens of motivation and acceptance.Frontiers in psychology · 2026Article
- On function-on-function linear quantile regression.Journal of applied statistics · 2025Article
- Quantile Regression for Longitudinal Functional Data with Application to Feed Intake of Lactating Sows.Journal of agricultural, biological, and environmental statistics · 2025Article
- A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures.Biometrics · 2024Article
- Robust scalar-on-function partial quantile regression.Journal of applied statistics · 2024Article
- FUNCTION-ON-SCALAR QUANTILE REGRESSION WITH APPLICATION TO MASS SPECTROMETRY PROTEOMICS DATA.The annals of applied statistics · 2020Article
- Quantile Function on Scalar Regression Analysis for Distributional Data.Journal of the American Statistical Association · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
In this paper, we study statistical inference in functional quantile regression for scalar response and a functional covariate. Specifically, we consider a functional linear quantile regression model where the effect of the covariate on the quantile of the response is modeled through the inner product between the functional covariate and an unknown smooth regression parameter function that varies with the level of quantile. The objective is to test that the regression parameter is constant across several quantile levels of interest. The parameter function is estimated by combining ideas from functional principal component analysis and quantile regression. An adjusted Wald testing procedure is proposed for this hypothesis of interest, and its chi-square asymptotic null distribution is derived. The testing procedure is investigated numerically in simulations involving sparse and noisy functional covariates and in a capital bike share data application. The proposed approach is easy to implement and the R code is published online at https://github.com/xylimeng/fQR-testing.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.