twSigmaLogitnorm
Estimating coefficients of logitnormal distribution from mode and given mu
twSigmaLogitnorm(mle, mu = 0)
mle |
numeric vector: the mode of the density function |
mu |
for mu = 0 the distribution will be the flattest case (maybe bimodal) |
For a mostly flat unimodal distribution use twCoefLogitnormMLE(mle,0)
numeric matrix with columns c("mu","sigma")
rows correspond to rows in mle and mu
Thomas Wutzler
mle <- 0.8 (theta <- twSigmaLogitnorm(mle)) # 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(mle),col = "gray") dx <- dlogitnorm(x,mu = theta[1],sigma = theta[2]) #density function plot(dx~x); abline(v = c(mle),col = "gray") # vectorized (theta <- twSigmaLogitnorm(mle = seq(0.401,0.8,by = 0.1)))
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