cdf2quantile

Inverse cumulative distribution function

Framework to fit distributional stochastic frontier models. Casts the stochastic frontier model into the flexible framework of distributional regression or otherwise known as General Additive Models of Location, Scale and Shape (GAMLSS). Allows for linear, non-linear, random and spatial effects on all the parameters of the distribution of the output, e.g. effects on the production or cost function, heterogeneity of the noise and inefficiency. Available distributions are the normal-halfnormal and normal-exponential distribution. Estimation via the fast and reliable routines of the 'mgcv' package. For more details see <doi:10.1016/j.csda.2023.107796>.

Rouven Schmidt

dsfa

Distributional Stochastic Frontier Analysis

cdf2quantile function

<dl><dt>p</dt>
<dd>numeric vector of probabilities.</dd>
<dt>cdf</dt>
<dd>function, cumulative distribution function which to invert.</dd>
<dt>interval</dt>
<dd>numeric vector of length 2, determining the lower and upper bound of the uniroot interval</dd>
<dt>...</dt>
<dd>other arguments for the cdf, e.g. mu, sigma_v, sigma_u, s...</dd></dl>

Arguments

Inverse cumulative distribution function — cdf2quantile

<dl>

<dt>p</dt>
<dd>numeric vector of probabilities.</dd>


<dt>cdf</dt>
<dd>function, cumulative distribution function which to invert.</dd>


<dt>interval</dt>
<dd>numeric vector of length 2, determining the lower and upper bound of the uniroot interval</dd>


<dt>...</dt>
<dd>other arguments for the cdf, e.g. mu, sigma_v, sigma_u, s...</dd>

</dl>

cdf2quantile: Inverse cumulative distribution function

Description

Usage

Value

Arguments

Details

Examples