Finds the best-fit beta distribution parameters for a given confidence interval for a probability parameter and returns the shape1, shape2 parameters.
identifyBetaPars(
qLow,
qUpp,
alpha = 0.05,
initPars = c(50, 50),
maxiter = 1000
)The observed lower quantile.
The observed upper quantile.
The confidence level; i.e. the desired coverage is 1-alpha. Defaults to 0.05.
A vector of length 2 giving the initial parameter values to start the optimisation; defaults to c(50,50).
Maximum number of iterations for optim. Defaults to 1e3. Set to higher values if convergence problems are reported.
A vector of length 2 giving the 2 parameters shape1 and shape1 for use with rbeta/dbeta/pbeta/qbeta.