twCoefLogitnormN
Estimating coefficients from a vector of quantiles and percentiles (non-vectorized).
twCoefLogitnormN(quant, perc = c(0.5, 0.975),
method = "BFGS", theta0 = c(mu = 0, sigma = 1),
returnDetails = FALSE, ...)quant |
the quantile values |
perc |
the probabilities for which the quantiles were specified |
method |
method of optimization (see |
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. |
named numeric vector with estimated parameters of the logitnormal distribution.
names: c("mu","sigma")
Thomas Wutzler
# 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")
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