cdfplot (Statistics Toolbox)

Plot of empirical cumulative distribution function

Syntax

cdfplot(X)
h = cdfplot(X)
[h,stats] = cdfplot(X)

Description

cdfplot(X) displays a plot of the empirical cumulative distribution function (cdf) for the data in the vector X. The empirical cdf is defined as the proportion of X values less than or equal to x.

This plot, like those produced by hist and normplot, is useful for examining the distribution of a sample of data. You can overlay a theoretical cdf on the same plot to compare the empirical distribution of the sample to the theoretical distribution.

The kstest, kstest2, and lillietest functions compute test statistics that are derived from the empirical cdf. You may find the empirical cdf plot produced by cdfplot useful in helping you to understand the output from those functions.

H = cdfplot(X) returns a handle to the cdf curve.

[h,stats] = cdfplot(X) also returns a stats structure with the following fields.

Field
Contents

stats.min
Minimum value

stats.max
Maximum value

stats.mean
Sample mean

stats.median
Sample median (50th percentile)

stats.std
Sample standard deviation

Field	Contents
`stats.min`	Minimum value
`stats.max`	Maximum value
`stats.mean`	Sample mean
`stats.median`	Sample median (50th percentile)
`stats.std`	Sample standard deviation

Examples

Generate a normal sample and an empirical cdf plot of the data.

```
x = normrnd(0,1,50,1);
cdfplot(x)
```

cdf chi2cdf