twCoefLogitnormMLE
Estimating coefficients of logitnormal distribution from mode and upper quantile
twCoefLogitnormMLE(mle, quant, perc = 0.999)
mle |
numeric vector: the mode of the density function |
quant |
numeric vector: the upper quantile value |
perc |
numeric vector: the probability for which the quantile was specified |
numeric matrix with columns c("mu","sigma")
rows correspond to rows in mle, quant, and perc
Thomas Wutzler
# estimate the parameters, with mode 0.7 and upper quantile 0.9 mode = 0.7; upper = 0.9 mode = 0.2; upper = 0.7 #mode = 0.5; upper = 0.9 (theta <- twCoefLogitnormMLE(mode,upper)) x <- seq(0,1,length.out = 41)[-c(1,41)] # plotting grid px <- plogitnorm(x,mu = theta[1],sigma = theta[2]) #percentiles function plot(px~x); abline(v = c(mode,upper),col = "gray"); abline(h = c(0.999),col = "gray") dx <- dlogitnorm(x,mu = theta[1],sigma = theta[2]) #density function plot(dx~x); abline(v = c(mode,upper),col = "gray") # vectorized (theta <- twCoefLogitnormMLE(mle = seq(0.4,0.8,by = 0.1),quant = upper)) # flat (theta <- twCoefLogitnormMLEFlat(mode))
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