Plotcqq: Difference between revisions
Jump to navigation
Jump to search
imported>Jeremy (Importing text file) |
imported>Jeremy |
||
| Line 1: | Line 1: | ||
===Purpose=== | ===Purpose=== | ||
| Line 11: | Line 10: | ||
Plots a conditional QQplot of a sample in vector (x). Conditional quantile plots as described in the 1986 Kafadar and Spiegelman article "An alternative to ordinary q-q plots" in Computational Statistics & Data Analysis are also available in this toolbox. | Plots a conditional QQplot of a sample in vector (x). Conditional quantile plots as described in the 1986 Kafadar and Spiegelman article "An alternative to ordinary q-q plots" in Computational Statistics & Data Analysis are also available in this toolbox. | ||
====Inputs==== | ====Inputs==== | ||
Revision as of 12:32, 9 October 2008
Purpose
Conditional quantile-quantile plot.
Synopsis
- vals = plotcqq(x,distname,translate)
Description
Plots a conditional QQplot of a sample in vector (x). Conditional quantile plots as described in the 1986 Kafadar and Spiegelman article "An alternative to ordinary q-q plots" in Computational Statistics & Data Analysis are also available in this toolbox.
Inputs
- x = matrix (column vector) in which the sample data is stored.
- distname = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'.
- translate = scalar, axis translation.
Outputs
The return value is a structure with the following fields:
- q = quantile of the named distribution.
- u = values at which the quantiles were evaluated.
Examples
vals = plotcqq(x)
vals = plotcqq(x,'normal')
vals = plotcqq(x,'beta')