postprocess_theta {ssmodels} | R Documentation |
Post-process Parameter Vector for Generalized Heckman Models
Description
Internal helper function that assigns meaningful names to a vector of estimated
parameters and applies transformations to sigma
and rho
parameters
to obtain interpretable estimates.
Usage
postprocess_theta(theta_par, NXS, NXO, NE, NV, XS, XO, outcomeS, outcomeC)
Arguments
theta_par |
A numeric vector containing the estimated parameters. |
NXS |
Integer. Number of covariates in the selection equation. |
NXO |
Integer. Number of covariates in the outcome equation. |
NE |
Integer. Number of covariates (or 1 for intercept-only) in the scale model. |
NV |
Integer. Number of covariates (or 1 for intercept-only) in the correlation model. |
XS |
Design matrix for the selection equation (used for naming). |
XO |
Design matrix for the outcome equation (used for naming). |
outcomeS |
Design matrix or variable for the scale (variance) model. |
outcomeC |
Design matrix or variable for the correlation model. |
Details
The parameter vector theta_par
is structured as follows:
The first
NXS
elements are coefficients for the selection equation.The next
NXO
elements are coefficients for the outcome equation.The next
NE
elements are coefficients (or log-sigma ifNE == 1
) for the scale model.The next
NV
elements are coefficients (or atanh(rho) ifNV == 1
) for the correlation model.
For interpretation, the function applies:
-
exp()
transformation forsigma
ifNE == 1
. -
tanh()
transformation forrho
ifNV == 1
.
Value
A named numeric vector with:
Transformed
sigma
andrho
values (if needed),Meaningful names assigned to all parameters.