cdf.compare
Compare Cumulative Distribution Functions

### Description

For a one sample problem, compares the empirical distribution function (edf) of the sample with a hypothesized cumulative distribution function. For a two sample problem, compares the edfs for the two samples. This graphical comparison is often useful before performing the Kolmogorov-Smirnov test (function ks.gof).

### Usage

    cdf.compare(x, y = NULL, distribution = "normal", ...)

### Arguments

x | numeric vector. NAs and Infs are allowed but will be removed.
y | numeric vector. NAs and Infs are allowed but will be removed.
distribution | character string that specifies the hypothesized distribution in the one sample test. For two samples, i.e. when y is specified, this argument is ignored. distribution can be one of: "normal", "beta", "cauchy", "chisquare", "exponential", "f", "gamma", "lognormal", "logistic", "t", "uniform", "weibull", "binomial", "geometric", "hypergeometric", "negbinomial", "poisson", or "wilcoxon". You need only supply the first characters that uniquely specify the distribution name. For example, "logn" and "logi" uniquely specify the lognormal and logistic distributions.
... | For one sample, parameter arguments for the function that generates p-values for the hypothesized distribution.

Side Effects
Produces a plot of the two compared cdfs on the current graphics device.
See Also
chisq.gof, ks.gof, ppoints (to create QQ plots), qqnorm, qqplot, rexp, rnorm.
Examples

    # one sample
    z <- rnorm(100)
    # compare with a normal distn:
    cdf.compare(z, dist = "normal")
    # compare with a chisquare distn.:
    cdf.compare(z, dist = "chisquare", df = 2)
    # two sample
    x <- rnorm(25)
    y <- rexp(100)
    cdf.compare(x, y)

Package terrUtils version 6.1.5-18
Package Index