twCoefLogitnormN: twCoefLogitnormN

In logitnorm: Functions for the Logitnormal Distribution

Description

Estimating coefficients from a vector of quantiles and percentiles (non-vectorized).

Usage

twCoefLogitnormN(quant, perc = c(0.5, 0.975), 
    method = "BFGS", theta0 = c(mu = 0, sigma = 1), 
    returnDetails = FALSE, ...)

Arguments

quant	the quantile values
perc	the probabilities for which the quantiles were specified
method	method of optimization (see optim)
theta0	starting parameters
returnDetails	if TRUE, the full output of optim is returned instead of only entry par
...	further parameters passed to optim, e.g. control = list(maxit = 1000)

Value

named numeric vector with estimated parameters of the logitnormal distribution. names: c("mu","sigma")

Author(s)

Thomas Wutzler

See Also

logitnorm

Examples

# experiment of re-estimation the parameters from generated observations
thetaTrue <- c(mu = 0.8, sigma = 0.7)
obsTrue <- rlogitnorm(thetaTrue["mu"],thetaTrue["sigma"], n = 500)
obs <- obsTrue + rnorm(100, sd = 0.05)        # some observation uncertainty
plot(density(obsTrue),col = "blue"); lines(density(obs))

# re-estimate parameters based on the quantiles of the observations
(theta <- twCoefLogitnorm( median(obs), quantile(obs,probs = 0.9), perc = 0.9))

# add line of estimated distribution
x <- seq(0,1,length.out = 41)[-c(1,41)]	# plotting grid
dx <- dlogitnorm(x,mu = theta[1],sigma = theta[2])
lines( dx ~ x, col = "orange")

logitnorm documentation built on Jan. 7, 2021, 9:09 a.m.