identifyNormPars: Determine the parameters of the best-fit normal / Gaussian...

In bootComb: Combine Parameter Estimates via Parametric Bootstrap

Description

Finds the best-fit normal distribution parameters for a given confidence interval and returns the mean and sd parameters.

Usage

identifyNormPars(qLow, qUpp, alpha = 0.05, initPars = c(0, 1), maxiter = 1000)

Arguments

qLow	The observed lower quantile.
qUpp	The observed upper quantile.
alpha	The confidence level; i.e. the desired coverage is 1-alpha. Defaults to 0.05.
initPars	A vector of length 2 giving the initial parameter values to start the optimisation; defaults to c(50,50).
maxiter	Maximum number of iterations for optim. Defaults to 1e3. Set to higher values if convergence problems are reported.

Value

A vector of length 2 giving the 2 parameters mean and sd for use with rnorm/dnorm/pnorm/qnorm.

See Also

ssNormPars, optim, dnorm

bootComb documentation built on Jan. 31, 2022, 1:07 a.m.