Results 1 to 10 of about 2,329,699 (248)

Functional coefficient quantile regression model with time-varying loadings

Journal of Applied Economics, 2023
This paper proposes a functional coefficient quantile regression model with heterogeneous and time-varying regression coefficients and factor loadings. Estimation of the model coefficients is done in two stages.
Alev Atak, Gabriel Montes-Rojas, Jose Olmo   +2 more
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Quantity quantiles linear regression [PDF]

Statistical Methods and Applications, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Paolo Radaelli, Michele Zenga
openaire   +3 more sources

Censored Quantile Regression Redux

Journal of Statistical Software, 2008
Quantile regression for censored survival (duration) data offers a more flexible alternative to the Cox proportional hazard model for some applications. We describe three estimation methods for such applications that have been recently incorporated into ...
Roger Koenker
doaj  

Probabilistic Solar Forecasting Using Quantile Regression Models

Energies, 2017
In this work, we assess the performance of three probabilistic models for intra-day solar forecasting. More precisely, a linear quantile regression method is used to build three models for generating 1 h–6 h-ahead probabilistic forecasts. Our approach is
Philippe Lauret, Mathieu David, Hugo T. C. Pedro   +2 more
doaj   +1 more source

Quantile cointegrating regression [PDF]

Journal of Econometrics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Unit-Modified Weibull Distribution and Quantile Regression Model [PDF]

Anais da Academia Brasileira de Ciências
The Sustainable Development Goals (SDGs) of the United Nations consist of 17 general objectives, subdivided into 169 targets to be achieved by 2030. Several SDG indices and indicators require continuous analysis and evaluation, and most of these indices ...
JOÃO INÁCIO SCRIMINI, CLEBER BISOGNIN, RENATA ROJAS GUERRA, FÁBIO M. BAYER   +3 more
doaj   +1 more source

An Improved Interior Point Algorithm for Quantile Regression

IEEE Access, 2020
Quantile regression is a powerful statistical technique for estimating the quantiles of a conditional distribution on the values of covariates. It has been widely used in many fields.
Pan Zhao, Shenghua Yu
doaj   +1 more source

Predictions in Quantile Regressions

Open Journal of Statistics, 2014
Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize forecast errors, and a fluctuation test to evaluate in-sample predictions. The scores of the PISA test to evaluate students’ proficiency are considered. Growth analysis relates school attainment to economic growth.
openaire   +3 more sources

Vector quantile regression [PDF]

We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y, taking values in ℝd given covariates Z=z, taking values in ℝk, is a map u↦QY∣Z(u,z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U
Guillaume Carlier, Victor Chernozhukov, Alfred Galichon   +2 more
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Conformalized Quantile Regression

, 2019
Conformal prediction is a technique for constructing prediction intervals that attain valid coverage in finite samples, without making distributional assumptions. Despite this appeal, existing conformal methods can be unnecessarily conservative because they form intervals of constant or weakly varying length across the input space.
Yaniv Romano, Evan Patterson, Emmanuel J. Candès   +2 more
openaire   +3 more sources