mom2par

Calculates the parameters of composed-error distribution based on the provided moments.

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

mom2par function

<dl><dt>mean</dt>
<dd>numeric vector of means.</dd>
<dt>sd</dt>
<dd>numeric vector of standard deviations. Must be positive.</dd>
<dt>skew</dt>
<dd>numeric vector of skewness. <code>s*skew</code> must be positive.</dd>
<dt>s</dt>
<dd>integer; \(s=-1\) for production and \(s=1\) for cost function.</dd>
<dt>distr</dt>
<dd>string; determines the distribution: 
`normhnorm`, Normal-halfnormal distribution 
`normexp`, Normal-exponential distribution </dd></dl>

Arguments

Moments to Parameters — mom2par

<dl>

<dt>mean</dt>
<dd>numeric vector of means.</dd>


<dt>sd</dt>
<dd>numeric vector of standard deviations. Must be positive.</dd>


<dt>skew</dt>
<dd>numeric vector of skewness. <code>s*skew</code> must be positive.</dd>


<dt>s</dt>
<dd>integer; \(s=-1\) for production and \(s=1\) for cost function.</dd>


<dt>distr</dt>
<dd>string; determines the distribution: 
`normhnorm`, Normal-halfnormal distribution 
`normexp`, Normal-exponential distribution </dd>

</dl>

mom2par: Moments to Parameters

Description

Usage

Value

Arguments

Details

Examples