twSigmaLogitnorm: twSigmaLogitnorm

In logitnorm: Functions for the Logitnormal Distribution

Description

Estimating coefficients of logitnormal distribution from mode and given mu

Usage

twSigmaLogitnorm(mle, mu = 0)

Arguments

mle	numeric vector: the mode of the density function
mu	for mu = 0 the distribution will be the flattest case (maybe bimodal)

Details

For a mostly flat unimodal distribution use twCoefLogitnormMLE(mle,0)

Value

numeric matrix with columns c("mu","sigma") rows correspond to rows in mle and mu

Author(s)

Thomas Wutzler

See Also

logitnorm

Examples

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)))

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