Results 1 to 10 of about 76,904 (164)
Function-on-function linear quantile regression
Mathematical Modelling and Analysis, 2022 In this study, we propose a function-on-function linear quantile regression model that allows for more than one functional predictor to establish a more flexible and robust approach. The proposed model is first transformed into a finitedimensional space
Ufuk Beyaztas, Han Lin Shang
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The generalized sigmoidal quantile function. [PDF]
Commun 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.
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An Investigation of Quantile Function Estimators Relative to Quantile Confidence Interval Coverage. [PDF]
Commun Stat Theory Methods, 2015 In this article, we investigate the limitations of traditional quantile function estimators and introduce a new class of quantile function estimators, namely, the semi-parametric tail-extrapolated quantile estimators, which has excellent performance for estimating the extreme tails with finite sample sizes.
Wei L, Wang D, Hutson AD.
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On function-on-function linear quantile regression
Journal of Applied StatisticsWe present two innovative functional partial quantile regression algorithms designed to accurately and efficiently estimate the regression coefficient function within the function-on-function linear quantile regression model. Our algorithms utilize functional partial quantile regression decomposition to effectively project the infinite-dimensional ...
Ufuk Beyaztaş +2 more
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Function-on-Function Partial Quantile Regression [PDF]
Journal 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
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Some Reliability Properties of Extropy and its Related Measures Using Quantile Function
Statistica, 2021 Extropy is a recent addition to the family of information measures as a complementary dual of Shannon entropy, to measure the uncertainty contained in a probability distribution of a random variable.
Aswathy Sree Krishnan +2 more
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Estimation for Extreme Conditional Quantiles of Functional Quantile Regression
Statistica 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
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A Truncated General-G Class of Distributions with Application to Truncated Burr-G Family
Revstat Statistical Journal, 2021 In this paper, we introduce a truncated general-G class of distributions. This class can be viewed as a weighted family of distributions with a general weight function, and also it generalizes the beta generator family proposed by Eugene et al.
Farrukh Jamal +2 more
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The Zografos-Balakrishnan Lindley Distribution: Properties and Applications
Statistica, 2021 The Lindley distribution was proposed in the context of Bayesian statistics as a counter example of fiducial statistics. In this paper, we propose Zografos Balakrishnan Lindley (ZBL) distribution in which Lindley distribution is a special case.
Muhammed Rasheed Irshad +2 more
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Multivariate Quantile Function Forecaster
CoRR, 2022 We propose Multivariate Quantile Function Forecaster (MQF$^2$), a global probabilistic forecasting method constructed using a multivariate quantile function and investigate its application to multi-horizon forecasting. Prior approaches are either autoregressive, implicitly capturing the dependency structure across time but exhibiting error accumulation
Kelvin Kan +6 more
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