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

## Description

Estimating coefficients of logitnormal distribution from median and upper quantile

## Usage

 ```1 2 3 4 5 6 7``` ```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

Thomas Wutzler

## See Also

`logitnorm`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34``` ```# 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[1],sigma=theta[2]) #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[1],sigma=theta[2]) #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)) ```

logitnorm documentation built on May 31, 2017, 4:45 a.m.