Results 221 to 230 of about 73,349 (260)

Nonparametric estimation of quantile density function

Computational Statistics and Data Analysis, 2012
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Pooja Soni, Isha Dewan, Kanchan Jain
exaly   +2 more sources

FUNCTIONAL ADDITIVE QUANTILE REGRESSION

Statistica Sinica, 2021
Summary: We investigate a functional additive quantile regression that models the conditional quantile of a scalar response based on the nonparametric effects of a functional predictor. We model the nonparametric effects of the principal component scores as additive components, which are approximated by B-splines.
Zhang, Yingying, Lian, Heng, Li, Guodong, Zhu, Zhongyi   +3 more
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Sketched quantile additive functional regression

Neurocomputing, 2021
Abstract The quantile additive functional regression (QAFR) relates the response to the integral of F ( t , X ( t ) ) over t, where F is an unknown function and X ( t ) is the predictor in the form of a curve (function). This model incorporates functional linear quantile regression as a special case and the appearance of ...
Yingying Zhang, Heng Lian
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Pseudo-quantile functional data clustering

Journal of Multivariate Analysis, 2020
This paper studies the problem of functional data clustering. Functional data are inherently infinite-dimensional, so classical clustering technique are not appropriate for them. A new approach for functional data clustering based on the concept of an asymetric norm is considered.
Joonpyo Kim, Hee-Seok Oh
openaire   +1 more source

Estimation of quantile density function based on regression quantiles

Statistics & Probability Letters, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dodge, Yadolah, Jurečková, Jana
openaire   +2 more sources

Statistical Modelling With Quantile Functions

Technometrics, 2001
(2001). Statistical Modelling With Quantile Functions. Technometrics: Vol. 43, No. 4, pp. 488-489.
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Simultaneous Functional Quantile Regression

Statistica Sinica
Summary: The conventional method for functional quantile regression (FQR) is to fit the regression model for each quantile of interest separately. Therefore, the slope function of the regression, as a bivariate function of time and quantile, is estimated as a univariate function of time for each fixed quantile. However, there are several limitations to
Hu, Boyi, Hu, Xixi, Liu, Hua, You, Jinhong, Cao, Jiguo   +4 more
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Risk preferences on the space of quantile functions

Mathematical Programming, 2013
The recent authors' paper [SIAM J. Optim. 23, No. 1, 381--405 (2013; Zbl 1271.91051)] provided a unified approach to two very popular theories, the theory of expected utility and the dual utility theory, by using tools of modern convex analysis. The aim of the present paper is to continue along the theory of the previous paper to develop a quantile ...
Darinka Dentcheva, Andrzej Ruszczynski
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Evaluating the Quantile and Density Quantile Function

1989
In this chapter (a) we start with the “pure” nonparametric, statistical model, (b) introduce smoothness conditions.
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