Distribution class of a squared normal distribution

Implementation of \(Z^2\), where \(Z\) is normally distributed with mean \(\mu\) and variance \(\sigma^2\). \(Z^2\) is chi-squared distributed with \(1\) degree of freedom and non-centrality parameter \((\mu/\sigma)^2\). The function get_tau_ZSquared computes the factor \(\tau=(\mu/\sigma)^2\), such that \(\tau\) is the equivalent of \(\theta\) in the normally distributed case. The square of a normal distribution \(Z^2\) can be used for two-sided hypothesis testing.

ZSquared(two_armed = TRUE)

get_tau_ZSquared(mu, sigma = 1)

Arguments

two_armed

logical indicating if a two-armed trial is regarded

mu

mean of Z

sigma

standard deviation of Z

Examples

zsquared <- ZSquared(FALSE)


H1 <- PointMassPrior(get_tau_ZSquared(0.4, 1), 1)