# twCoefLogitnorm: twCoefLogitnorm In logitnorm: Functions for the Logitnormal Distribution

## Description

Estimating coefficients of logitnormal distribution from median and upper quantile

## Usage

 ```1 2 3``` ```twCoefLogitnorm(median, quant, perc = 0.975, method = "BFGS", theta0 = c(mu = 0, sigma = 1), returnDetails = FALSE, ...) ```

## Arguments

 `median` numeric vector: the median of the density function `quant` numeric vector: the upper quantile value `perc` numeric vector: the probability for which the quantile was specified `method` method of optimization (see `optim`) `theta0` starting parameters `returnDetails` if TRUE, the full output of optim is attached as attributes resOptim `...`

## Value

numeric matrix with columns `c("mu","sigma")` rows correspond to rows in median, quant, and perc

## Author(s)

Thomas Wutzler

`logitnorm`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```# estimate the parameters, with median at 0.7 and upper quantile at 0.9 (theta <- twCoefLogitnorm(0.7,0.9)) x <- seq(0,1,length.out = 41)[-c(1,41)] # plotting grid px <- plogitnorm(x,mu = theta,sigma = theta) #percentiles function plot(px~x); abline(v = c(0.7,0.9),col = "gray"); abline(h = c(0.5,0.975),col = "gray") dx <- dlogitnorm(x,mu = theta,sigma = theta) #density function plot(dx~x); abline(v = c(0.7,0.9),col = "gray") # vectorized (theta <- twCoefLogitnorm(seq(0.4,0.8,by = 0.1),0.9)) ```