Quantile regression with bootstrapping confidence intervals
Updated 16 Mar 2015

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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

Cite As

Aslak Grinsted (2024). quantreg(x,y,tau,order,Nboot) (https://www.mathworks.com/matlabcentral/fileexchange/32115-quantreg-x-y-tau-order-nboot), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired: Non-crossing polynomial quantile regression

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Version Published Release Notes

implemented suggested change from Simeon Yurek in a FEX comment

Fixed another small bug.

Fixed a few issues with input parameter parsing.