Quantile regression with bootstrapping confidence intervals

5.6K descargas

Actualizado 16 Mar 2015

Ver licencia

Quantile Regression

USAGE: [p,stats]=quantreg(x,y,tau[,order,nboot]);

x,y: data that is fitted. (x and y should be columns)
Note: that if x is a matrix with several columns then multiple
linear regression is used and the "order" argument is not used.
tau: quantile used in regression.
order: polynomial order. (default=1)
nboot: number of bootstrap surrogates used in statistical inference.(default=200)

stats is a structure with the following fields:
.pse: standard error on p. (not independent)
.pboot: the bootstrapped polynomial coefficients.
.yfitci: 95% confidence interval on polyval(p,x)

Note: uses bootstrap on residuals for statistical inference. (see help bootstrp)
check also: http://www.econ.uiuc.edu/~roger/research/intro/rq.pdf

legend('data','2nd order 90th percentile fit','95% confidence interval','location','best')

For references on the method check e.g. and refs therein:

Copyright (C) 2008, Aslak Grinsted

Citar como

Aslak Grinsted (2023). quantreg(x,y,tau,order,Nboot) (https://www.mathworks.com/matlabcentral/fileexchange/32115-quantreg-x-y-tau-order-nboot), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R14
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

Inspiración para: Non-crossing polynomial quantile regression

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Versión Publicado Notas de la versión

implemented suggested change from Simeon Yurek in a FEX comment

Fixed another small bug.

Fixed a few issues with input parameter parsing.