print.summary.snreg

Prints the contents of a <code>"summary.snreg"</code> object in a structured
format. The method reports convergence status (based on gradient-Hessian
scaling), log-likelihood, estimation results, and—when present—summaries
for technical/cost efficiencies and marginal effects.

Models with skew‑normally distributed and thus asymmetric error terms, implementing the methods developed in Badunenko and Henderson (2023) "Production analysis with asymmetric noise" <doi:10.1007/s11123-023-00680-5>. The package provides tools to estimate regression models with skew‑normal error terms, allowing both the variance and skewness parameters to be heteroskedastic. It also includes a stochastic frontier framework that accommodates both i.i.d. and heteroskedastic inefficiency terms.

Oleg Badunenko

snreg

Regression with Skew-Normally Distributed Error Term

John Burkardt

print.summary.snreg function

<dl><dt>x</dt>
<dd>an object of class <code>"summary.snreg"</code> (produced by <code>summary.snreg</code>).</dd>
<dt>digits</dt>
<dd>integer indicating the number of digits to print; default <code>NULL</code>
(internally set to 4).</dd>
<dt>...</dt>
<dd>additional arguments (currently unused).</dd></dl>

Arguments

Print Summary of snreg Results — print.summary.snreg

<dl>

<dt>x</dt>
<dd>an object of class <code>"summary.snreg"</code> (produced by <code>summary.snreg</code>).</dd>


<dt>digits</dt>
<dd>integer indicating the number of digits to print; default <code>NULL</code>
(internally set to 4).</dd>


<dt>...</dt>
<dd>additional arguments (currently unused).</dd>

</dl>

print.summary.snreg: Print Summary of snreg Results

Description

Usage

Value

Arguments

Details

See Also