fetch.rho.b

The model has a correlation parameter which is estimated and theoretically bound between -1 and +1. To ensure that the estimated parameters are within the theoretical bounds a transformation is necessary. The chosen transformation is: 	
$$f(\rho): \rho = \frac{2}{(1-exp(-\theta))}- 1$$	
Whereas $\rho$ is the actual correlation coefficient and $\theta$ is the parameter we estimate in the model. This parametrization has been worked into the likelihood function and ensures that $\rho$ will be between $-1$ and $+1$.

transformation

correlation coefficient

Provides functions to estimate a strategic selection estimator. A strategic selection estimator is an agent error model in which the two random components are not assumed to be orthogonal. In addition this package provides generic functions to print and plot objects of its class as well as the necessary functions to create tables for LaTeX. There is also a function to create dyadic data sets.

Lucas Leemann

StratSel

Strategic Selection Estimator

fetch.rho.b function

<dl> <dt>b</dt>
<dd>The vector of estimated coefficients ($\beta$) whereas the last element is the transformed correlation coefficient (here: $\theta$).
</dd></dl>

Arguments

Lucas Leemann <a href="/link/lleemann%40gmail.com?package=StratSel&version=1.4" data-mini-rdoc="StratSel::lleemann@gmail.com">lleemann@gmail.com</a>

Author

The model has a correlation parameter which is estimated and theoretically bound between -1 and +1. To ensure that the estimated parameters are within the theoretical bounds a transformation is necessary. The chosen transformation is: 	
$$f(\rho): \rho = \frac{2}{(1-exp(-\theta))}- 1$$	
Whereas $\rho$ is the actual correlation coefficient and $\theta$ is the parameter we estimate in the model. This parametrization has been worked into the likelihood function and ensures that $\rho$ will be between $-1$ and $+1$.

Function to transform f($\rho$) back to $\rho$
 — fetch.rho.b

<dl>

 <dt>b</dt>
<dd>The vector of estimated coefficients ($\beta$) whereas the last element is the transformed correlation coefficient (here: $\theta$).
</dd>

</dl>

Lucas Leemann <a href='mailto:lleemann@gmail.com'>lleemann@gmail.com</a>

fetch.rho.b: Function to transform f(\(\rho\)) back to \(\rho\)

Description

Usage

Value

Arguments

Author

Details

See Also

Examples