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| Package: logitnorm | ||
| Title: Functions for the Logitnormal Distribution | ||
| Version: 0.8.37 | ||
| Version: 0.8.38 | ||
| Author: Thomas Wutzler | ||
| Maintainer: Thomas Wutzler <[email protected]> | ||
| Description: Density, distribution, quantile and random generation function for the logitnormal distribution. Estimation of the mode and the first two moments. Estimation of distribution parameters. | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,56 +1,56 @@ | ||
| --- | ||
| output: github_document | ||
| --- | ||
|
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| <!-- | ||
| README.md is generated from README.Rmd. Please edit that file | ||
| knitr::knit("README.Rmd") | ||
| --> | ||
|
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||
|
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||
| ```{r, echo = FALSE} | ||
| knitr::opts_chunk$set( | ||
| collapse = TRUE, | ||
| comment = "#>", | ||
| fig.path = "tools/README-" | ||
| ) | ||
| ``` | ||
|
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||
| [](http://cran.r-project.org/package=logitnorm) | ||
| [](https://travis-ci.org/bgctw/logitnorm) | ||
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| ## Overview | ||
|
|
||
| `logitnorm` package provides support for the univariate | ||
| [logit-normal | ||
| distribution](https://en.wikipedia.org/wiki/Logit-normal_distribution). In | ||
| addition to the usual random, density, percential, and quantile function, it | ||
| helps with estimating distribution parameters from observations statistics. | ||
|
|
||
| ## Installation | ||
|
|
||
| ```{r, eval = FALSE} | ||
| # From CRAN | ||
| install.packages("logitnorm") | ||
| # Or the the development version from GitHub: | ||
| # install.packages("devtools") | ||
| devtools::install_github("bgctw/logitnorm") | ||
| ``` | ||
|
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||
| ## Usage | ||
|
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||
| See the package vignette for an introduction. | ||
|
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||
| A simple example estimates distribution parameters from observation | ||
| statistics of mode 0.7 and upper quantile 0.9. Next, the density is | ||
| computed and plotted across a range of quantiles. | ||
|
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||
| ```{r example} | ||
| (theta <- twCoefLogitnormMLE(0.7,0.9)) | ||
| x <- seq(0,1, length.out=81) | ||
| d <- dlogitnorm(x, mu=theta[1,"mu"], sigma=theta[1,"sigma"]) | ||
| plot(d~x,type="l") | ||
| abline(v=c(0.7,0.9), col="grey") | ||
| ``` | ||
| --- | ||
| output: github_document | ||
| --- | ||
|
|
||
| <!-- | ||
| README.md is generated from README.Rmd. Please edit that file | ||
| knitr::knit("README.Rmd") | ||
| --> | ||
|
|
||
|
|
||
| ```{r, echo = FALSE} | ||
| knitr::opts_chunk$set( | ||
| collapse = TRUE, | ||
| comment = "#>", | ||
| fig.path = "tools/README-" | ||
| ) | ||
| ``` | ||
|
|
||
| [](http://cran.r-project.org/package=logitnorm) | ||
| [](https://travis-ci.org/bgctw/logitnorm) | ||
|
|
||
|
|
||
| ## Overview | ||
|
|
||
| `logitnorm` package provides support for the univariate | ||
| [logit-normal | ||
| distribution](https://en.wikipedia.org/wiki/Logit-normal_distribution). In | ||
| addition to the usual random, density, percentile, and quantile function, it | ||
| helps with estimating distribution parameters from observations statistics. | ||
|
|
||
| ## Installation | ||
|
|
||
| ```{r, eval = FALSE} | ||
| # From CRAN | ||
| install.packages("logitnorm") | ||
| # Or the the development version from GitHub: | ||
| # install.packages("devtools") | ||
| devtools::install_github("bgctw/logitnorm") | ||
| ``` | ||
|
|
||
| ## Usage | ||
|
|
||
| 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. | ||
|
|
||
| ```{r example} | ||
| (theta <- twCoefLogitnormMLE(0.7,0.9)) | ||
| x <- 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") | ||
| ``` |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,56 +1,56 @@ | ||
| --- | ||
| output: github_document | ||
| --- | ||
|
|
||
| <!-- | ||
| README.md is generated from README.Rmd. Please edit that file | ||
| knitr::knit("README.Rmd") | ||
| --> | ||
|
|
||
|
|
||
|
|
||
|
|
||
| [](http://cran.r-project.org/package=logitnorm) | ||
| [](https://travis-ci.org/bgctw/logitnorm) | ||
|
|
||
|
|
||
| ## Overview | ||
|
|
||
| `logitnorm` package provides support for the univariate | ||
| [logit-normal | ||
| distribution](https://en.wikipedia.org/wiki/Logit-normal_distribution). In | ||
| addition to the usual random, density, percential, and quantile function, it | ||
| helps with estimating distribution parameters from observations statistics. | ||
|
|
||
| ## Installation | ||
|
|
||
|
|
||
| ```r | ||
| # From CRAN | ||
| install.packages("logitnorm") | ||
|
|
||
| # Or the the development version from GitHub: | ||
| # install.packages("devtools") | ||
| devtools::install_github("bgctw/logitnorm") | ||
| ``` | ||
|
|
||
| ## Usage | ||
|
|
||
| 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. | ||
|
|
||
|
|
||
| ```r | ||
| (theta <- twCoefLogitnormMLE(0.7,0.9)) | ||
| #> mu sigma | ||
| #> [1,] 0.7608886 0.464783 | ||
| x <- 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") | ||
| ``` | ||
|
|
||
|  | ||
| --- | ||
| output: github_document | ||
| --- | ||
|
|
||
| <!-- | ||
| README.md is generated from README.Rmd. Please edit that file | ||
| knitr::knit("README.Rmd") | ||
| --> | ||
|
|
||
|
|
||
|
|
||
|
|
||
| [](http://cran.r-project.org/package=logitnorm) | ||
| [](https://travis-ci.org/bgctw/logitnorm) | ||
|
|
||
|
|
||
| ## Overview | ||
|
|
||
| `logitnorm` package provides support for the univariate | ||
| [logit-normal | ||
| distribution](https://en.wikipedia.org/wiki/Logit-normal_distribution). In | ||
| addition to the usual random, density, percentile, and quantile function, it | ||
| helps with estimating distribution parameters from observations statistics. | ||
|
|
||
| ## Installation | ||
|
|
||
|
|
||
| ```r | ||
| # From CRAN | ||
| install.packages("logitnorm") | ||
|
|
||
| # Or the the development version from GitHub: | ||
| # install.packages("devtools") | ||
| devtools::install_github("bgctw/logitnorm") | ||
| ``` | ||
|
|
||
| ## Usage | ||
|
|
||
| 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. | ||
|
|
||
|
|
||
| ```r | ||
| (theta <- twCoefLogitnormMLE(0.7,0.9)) | ||
| #> Error in twCoefLogitnormMLE(0.7, 0.9): could not find function "twCoefLogitnormMLE" | ||
| x <- seq(0,1, length.out=81) | ||
| d <- dlogitnorm(x, mu=theta[1,"mu"], sigma=theta[1,"sigma"]) | ||
| #> Error in dlogitnorm(x, mu = theta[1, "mu"], sigma = theta[1, "sigma"]): could not find function "dlogitnorm" | ||
| plot(d~x,type="l") | ||
| #> Error in eval(predvars, data, env): object 'd' not found | ||
| abline(v=c(0.7,0.9), col="grey") | ||
| #> Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet | ||
| ``` |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,34 +1,34 @@ | ||
| \name{dlogitnorm} | ||
| \alias{dlogitnorm} | ||
| \title{dlogitnorm} | ||
| \description{Density function of logitnormal distribution } | ||
| \usage{dlogitnorm(x, mu = 0, sigma = 1, log = FALSE, | ||
| ...)} | ||
| \arguments{ | ||
| \item{x}{vector of quantiles} | ||
| \item{mu}{distribution parameters} | ||
| \item{sigma}{ | ||
| } | ||
| \item{log}{if TRUE, the log-density is returned} | ||
| \item{\dots}{further arguments passed to \code{\link{dnorm}}: \code{mean}, | ||
| and \code{sd} for mu and sigma respectively. } | ||
| } | ||
| \details{\describe{\item{Logitnorm distribution}{ | ||
| \itemize{ | ||
| \item{density function: dlogitnorm } | ||
| \item{distribution function: \code{\link{plogitnorm}} } | ||
| \item{quantile function: \code{\link{qlogitnorm}} } | ||
| \item{random generation function: \code{\link{rlogitnorm}} } | ||
| } | ||
| }} | ||
|
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| The function is only defined in interval (0,1), but the density | ||
| returns 0 outside the support region.} | ||
|
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|
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| \author{Thomas Wutzler} | ||
|
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| \seealso{\code{\link{logitnorm}}} | ||
|
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| \name{dlogitnorm} | ||
| \alias{dlogitnorm} | ||
| \title{dlogitnorm} | ||
| \description{Density function of logitnormal distribution } | ||
| \usage{dlogitnorm(x, mu = 0, sigma = 1, log = FALSE, | ||
| ...)} | ||
| \arguments{ | ||
| \item{x}{vector of quantiles} | ||
| \item{mu}{distribution parameters} | ||
| \item{sigma}{ | ||
| } | ||
| \item{log}{if TRUE, the log-density is returned} | ||
| \item{\dots}{further arguments passed to \code{\link{dnorm}}: \code{mean}, | ||
| and \code{sd} for mu and sigma respectively. } | ||
| } | ||
| \details{\describe{\item{Logitnorm distribution}{ | ||
| \itemize{ | ||
| \item{density function: dlogitnorm } | ||
| \item{distribution function: \code{\link{plogitnorm}} } | ||
| \item{quantile function: \code{\link{qlogitnorm}} } | ||
| \item{random generation function: \code{\link{rlogitnorm}} } | ||
| } | ||
| }} | ||
|
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||
| The function is only defined in interval (0,1), but the density | ||
| returns 0 outside the support region.} | ||
|
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|
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| \author{Thomas Wutzler} | ||
|
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||
|
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|
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| \seealso{\code{\link{logitnorm}}} | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,22 +1,22 @@ | ||
| \name{invlogit} | ||
| \alias{invlogit} | ||
| \title{invlogit} | ||
| \description{Transforming (-Inf,Inf) to original scale (0,1)} | ||
| \usage{invlogit(q, ...)} | ||
| \arguments{ | ||
| \item{q}{ | ||
| } | ||
| \item{\dots}{ | ||
| } | ||
| } | ||
| \details{function \eqn{f(z) = \frac{e^{z}}{e^{z} + 1} \! = \frac{1}{1 + e^{-z}} \!}} | ||
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| \author{Thomas Wutzler} | ||
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| \seealso{\code{\link{logit}} | ||
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| \code{\link{logitnorm}}} | ||
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| \name{invlogit} | ||
| \alias{invlogit} | ||
| \title{invlogit} | ||
| \description{Transforming (-Inf,Inf) to original scale (0,1)} | ||
| \usage{invlogit(q, ...)} | ||
| \arguments{ | ||
| \item{q}{ | ||
| } | ||
| \item{\dots}{ | ||
| } | ||
| } | ||
| \details{function \eqn{f(z) = \frac{e^{z}}{e^{z} + 1} \! = \frac{1}{1 + e^{-z}} \!}} | ||
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| \author{Thomas Wutzler} | ||
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| \seealso{\code{\link{logit}} | ||
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| \code{\link{logitnorm}}} | ||
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