Results 121 to 130 of about 76,904 (164)

Nonparametric estimation of quantile density function

Computational Statistics and Data Analysis, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kanchan Jain, Pooja Soni, Isha Dewan
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
openaire   +1 more source

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
openaire   +1 more source

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

Statistical Modelling With Quantile Functions

Technometrics, 2001
(2001). Statistical Modelling With Quantile Functions. Technometrics: Vol. 43, No. 4, pp. 488-489.
openaire   +2 more sources

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

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
openaire   +2 more sources