Computes the column vector of the Inverse Mills Ratio (IMR) from
a Probit selection equation.

In order to facilitate the adjustment of the sample selection models
existing in the literature, we created the 'ssmodels' package. Our package
allows the adjustment of the classic Heckman model (Heckman (1976),
Heckman (1979) <doi:10.2307/1912352>), and the estimation of the parameters of
this model via the maximum likelihood method and two-step method, in addition
to the adjustment of the Heckman-t models introduced in the literature by
Marchenko and Genton (2012) <doi:10.1080/01621459.2012.656011> and the
Heckman-Skew model introduced in the literature by Ogundimu and Hutton (2016)
<doi:10.1111/sjos.12171>. We also implemented functions to adjust the
generalized version of the Heckman model, introduced by Bastos, Barreto-Souza,
and Genton (2021) <doi:10.5705/ss.202021.0068>, that allows the inclusion of
covariables to the dispersion and correlation parameters, and a function to
adjust the Heckman-BS model introduced by Bastos and Barreto-Souza (2020)
<doi:10.1080/02664763.2020.1780570> that uses the Birnbaum-Saunders
distribution as a joint distribution of the selection and primary regression
variables. This package extends and complements existing R packages such as
'sampleSelection' (Toomet and Henningsen, 2008) and 'ssmrob' (Zhelonkin et al., 2016), providing additional robust and flexible sample selection models.

Fernando de Souza Bastos

ssmodels

Sample Selection Models

Wagner Barreto de Souza

IMR function

<dl><dt>selection</dt>
<dd>A formula specifying the selection equation.</dd>
<dt>data</dt>
<dd>A data frame containing the variables in the model.</dd></dl>

Arguments

Inverse Mills Ratio (IMR) Calculation — IMR

<dl>

<dt>selection</dt>
<dd>A formula specifying the selection equation.</dd>


<dt>data</dt>
<dd>A data frame containing the variables in the model.</dd>

</dl>

IMR: Inverse Mills Ratio (IMR) Calculation

Description

Usage

Value

Arguments

Details

Examples