ZSquared-class: Distribution class of a squared normal distribution

In adoptr: Adaptive Optimal Two-Stage Designs

Distribution class of a squared normal distribution

Description

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.

Usage

ZSquared(two_armed = TRUE)

get_tau_ZSquared(mu, sigma)

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)

adoptr documentation built on Oct. 3, 2024, 1:08 a.m.