Chi-Squared data distribution

Implements a chi-squared distribution. The classes Pearson2xk and ZSquared are subclasses, used in two different situations. Pearson2xK is used when testing k groups for homogeneity in response rates. The null hypothesis is r₁=...=r_k, and the alternative is that there exists a pair of groups with differing rates. ZSquared implements the square of a normally distributed random variable with mean \(\mu\) and standard deviation \(\sigma^2\).

ChiSquared(df)

# S4 method for ChiSquared
quantile(x, probs, n, theta, ...)

# S4 method for ChiSquared,numeric
simulate(object, nsim, n, theta, seed = NULL, ...)

Arguments

df

number of degrees of freedom

x

outcome

probs

vector of probabilities

n

sample size

theta

distribution parameter

...

further optional arguments

object

object of class ChiSquared

nsim

number of simulation runs

seed

random seed

See also

see probability_density_function and cumulative_distribution_function to evaluate the pdf and the cdf, respectively.

Examples

datadist <- ChiSquared(df=4)