grad_msel

Calculates gradient of the log-likelihood function of 
multivariate ordered probit model.

Estimate the parameters of multivariate endogenous switching and sample selection models using methods described in Newey (2009) <doi:10.1111/j.1368-423X.2008.00263.x>, E. Kossova, B. Potanin (2018) <https://ideas.repec.org/a/ris/apltrx/0346.html>, E. Kossova, L. Kupriianova, B. Potanin (2020) <https://ideas.repec.org/a/ris/apltrx/0391.html> and E. Kossova, B. Potanin (2022) <https://ideas.repec.org/a/ris/apltrx/0455.html>.

Potanin Bogdan

switchSelection

Endogenous Switching and Sample Selection Regression Models

Bogdan Potanin

Sofiia Dolgikh

grad_msel function

<dl><dt>par</dt>
<dd>vector of parameters.</dd>
<dt>control_lnL</dt>
<dd>list with some additional parameters.</dd>
<dt>out_type</dt>
<dd>string representing the output type of the function.</dd>
<dt>n_sim</dt>
<dd>the number of random draws for multivariate 
normal probabilities.</dd>
<dt>n_cores</dt>
<dd>the number of cores to be used.</dd>
<dt>regularization</dt>
<dd>list of regularization parameters.</dd></dl>

Arguments

Gradient of the Log-likelihood Function of Multivariate Ordered
Probit Model — grad_msel

<dl>

<dt>par</dt>
<dd>vector of parameters.</dd>


<dt>control_lnL</dt>
<dd>list with some additional parameters.</dd>


<dt>out_type</dt>
<dd>string representing the output type of the function.</dd>


<dt>n_sim</dt>
<dd>the number of random draws for multivariate 
normal probabilities.</dd>


<dt>n_cores</dt>
<dd>the number of cores to be used.</dd>


<dt>regularization</dt>
<dd>list of regularization parameters.</dd>

</dl>

grad_msel: Gradient of the Log-likelihood Function of Multivariate Ordered Probit Model

Description

Usage

Arguments