Density, distribution, quantile and random generation function for the logitnormal distribution. Estimation of the mode and the first two moments. Estimation of distribution parameters.
logitnorm package provides support for the univariate
addition to the usual random, density, percential, and quantile function, it
helps with estimating distribution parameters from observations statistics.
# From CRANinstall.packages("logitnorm")# Or the the development version from GitHub:# install.packages("devtools")devtools::install_github("bgctw/logitnorm")
See the package vignette for an introduction.
A simple example estimates distribution parameters from observation statistics of mode 0.7 and upper quantile 0.9. Next, the density is computed and plotted across a range of quantiles.
(theta <- twCoefLogitnormMLE(0.7,0.9))#> mu sigma#> [1,] 0.7608886 0.464783x <- seq(0,1, length.out=81)d <- dlogitnorm(x, mu=theta[1,"mu"], sigma=theta[1,"sigma"])plot(d~x,type="l")abline(v=c(0.7,0.9), col="grey")
Remove the library call to MASS.
Avoid writing file reports during testing and installation.
Thanks to @madeleine-empirical the density function
dlogitnorm now has
log an argument that allows computing the density directly at log-scale.
The hosting of the development moved from r-forge to github. Releases will still be put to r-forge, because of its good package-checking setup for several platforms, and the help for submission to CRAN, but versioning and development of the code will be done on github.
A package vignette, a README.Rmd and this NEWS.md file have been added.