@article {Lodder:1988-11-01T00:00:00:0003-7028:1512,
author = "Lodder, Robert A. and Hieftje, Gary M.",
title = "Quantile Analysis: A Method for Characterizing Data Distributions",
journal = "Applied Spectroscopy",
volume = "42",
number = "8",
year = "1988-11-01T00:00:00",
abstract = "Analyzing distributions of data represents a common problem in chemistry. Quantile-quantile (QQ) plots provide a useful way to attack this problem. These graphs are often used in the form of the normal probability plot, to determine whether the residuals from a fitting process are randomly
distributed and therefore whether an assumed model fits the data at hand. By comparing the integrals of two probability density functions in a single plot, QQ plotting methods are able to capture the location, scale, and skew of a data set. This procedure provides more information to the analyst
than do classical statistical methods that rely on a single test statistic for distribution comparisons.",
pages = "1512-1520",
url = "http://www.ingentaconnect.com/content/sas/sas/1988/00000042/00000008/art00026",
doi = "doi:10.1366/0003702884429724",
keyword = "Near-infrared, Chemometrics"
}