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Estimation of Non-Unique Quantiles [PDF]
The Annals of Mathematical Statistics, 1966 This paper is concerned with consistent estimates of a quantile of a distribution function when the quantile is not unique. To be more precise, since the quantile is assumed not to be unique, we are concerned with obtaining a consistent estimate of the smallest $p$th quantile for a fixed $p(0 < p < 1)$, and from this procedure we can estimate the ...
Dorian Feldman, Howard G. Tucker
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Noncrossing quantile regression curve estimation [PDF]
Biometrika, 2010 Since quantile regression curves are estimated individually, the quantile curves can cross, leading to an invalid distribution for the response. A simple constrained version of quantile regression is proposed to avoid the crossing problem for both linear and nonparametric quantile curves.
Howard D. Bondell +2 more
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Estimation of quantile regression model without longitudinal data and with auxiliary information
Xi'an Gongcheng Daxue xuebao, 2021 In order to study the estimation of the quantile regression model with missing longitudinal data and auxiliary information, the parameter estimation and asymptotic normality of linear quantile regression model are given by using inverse probability ...
Yuting ZHANG +2 more
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Active Learning Strategy for Surrogate-Based Quantile Estimation of Field Function
Applied Sciences, 2022 Uncertainty quantification is widely used in engineering domains to provide confidence measures on complex systems. It often requires to accurately estimate extreme statistics on computationally intensive black-box models.
Loïc Brevault +2 more
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Mathematics, 2023 The presence of nonignorable missing response variables often leads to complex conditional distribution patterns that cannot be effectively captured through mean regression.
Jingxuan Guo +7 more
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Estimating Tukey depth using incremental quantile estimators
Pattern Recognition, 2022 The concept of depth represents methods to measure how deep an arbitrary point is positioned in a dataset and can be seen as the opposite of outlyingness. It has proved very useful and a wide range of methods have been developed based on the concept.
Hammer, Hugo Lewi +2 more
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Small Area Quantile Estimation [PDF]
International Statistical Review, 2018 SummarySample surveys are widely used to obtain information about totals, means, medians and other parameters of finite populations. In many applications, similar information is desired for subpopulations such as individuals in specific geographic areas and socio‐demographic groups. When the surveys are conducted at national or similarly high levels, a
Jiahua Chen, Yukun Liu
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Journal of Biostatistics and Epidemiology, 2023 Introduction: Quantile regression is a valuable alternative for survival data analysis, enabling flexible evaluations of covariate effects on survival outcomes with intuitive interpretations. It offers practical computation and reliability.
Fereshteh Mokhtarpour +3 more
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Desimal, 2023 The censored quantile regression method is a parameter estimation method that can be used to overcome censored data and BLUE (Best Linear Unbiased Estimator) assumptions that are not met.
Sarmada Sarmada +2 more
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Factors Affecting Productivity of Upland and Lowland Rice Farms in Matalom, Leyte: A Quantile Regression Approach [PDF]
Review of Socio-Economic Research and Development Studies, 2017 This study investigates the determinants of productivity in selected upland and lowland rice farms in Matalom, Leyte using quantile regression approach. Data on rice production are obtained from 40 upland and 40 lowland rice farming households which are ...
Brenda M. Ramoneda, Junnel K. Pene
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