Results 11 to 20 of about 204,570 (278)

The generalized sigmoidal quantile function. [PDF]

open access: yesCommun Stat Simul Comput, 2022
In this note we introduce a new smooth nonparametric quantile function estimator based on a newly defined generalized expectile function and termed the sigmoidal quantile function estimator. We also introduce a hybrid quantile function estimator, which combines the optimal properties of the classic kernel quantile function estimator with our new ...
Hutson AD.
europepmc   +4 more sources

Function-on-Function Partial Quantile Regression [PDF]

open access: yesJournal of Agricultural, Biological and Environmental Statistics, 2021
30 pages, 5 figures, to appear at the Journal of Agricultural, Biological and Environmental ...
Ufuk Beyaztas, Han Lin Shang, Aylin Alin
openaire   +6 more sources

Estimation for Extreme Conditional Quantiles of Functional Quantile Regression

open access: yesStatistica Sinica, 2023
Quantile regression as an alternative to modeling the conditional mean function provides a comprehensive picture of the relationship between a response and covariates. It is particularly attractive in applications focused on the upper or lower conditional quantiles of the response. However, conventional quantile regression estimators are often unstable
Zhu, Hanbing   +3 more
openaire   +2 more sources

Dynamic Quantile Function Models [PDF]

open access: yesSSRN Electronic Journal, 2017
Motivated by the need for effectively summarising, modelling, and forecasting the distributional characteristics of intra-daily returns, as well as the recent work on forecasting histogram-valued time-series in the area of symbolic data analysis, we develop a time-series model for forecasting quantile-function-valued (QF-valued) daily summaries for ...
Wilson Ye Chen   +3 more
openaire   +2 more sources

Inference in functional linear quantile regression

open access: yesJournal of Multivariate Analysis, 2022
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 ...
Meng Li   +3 more
openaire   +4 more sources

Transformed Log-Burr III Distribution: Structural Features and Application to Milk Production

open access: yesEngineering Proceedings, 2023
The Burr III distribution is extended in this work as a substitute for the numerous Burr III distributions. A new distribution is developed by applying the log transformation technique to define the transformed log-Burr III distribution.
Aliyu Ismail Ishaq   +4 more
doaj   +1 more source

The Nakagami–Weibull distribution in modeling real-life data

open access: yesCumhuriyet Science Journal, 2021
In this article, a four-parameter Nakagami Weibull distributions (NW) is proposed. We study a few statistical properties such as quantile function, moments, moment generating function, entropy, and order statistics have been derived.
İbrahim Abdullahi
doaj   +1 more source

Quantile correlations and quantile autoregressive modeling [PDF]

open access: yes, 2012
In this paper, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two valuable quantities, the quantile autocorrelation ...
Li, Guodong, Li, Yang, Tsai, Chih-Ling
core   +1 more source

Robust scalar-on-function partial quantile regression [PDF]

open access: yesJournal of Applied Statistics, 2023
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).
Ufuk Beyaztas, Mujgan Tez, Han Lin Shang
openaire   +3 more sources

Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification

open access: yesEconometrics, 2015
Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
doaj   +1 more source

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