print.cre

Prints a brief summary of the CRE object

Provides a new method for interpretable heterogeneous
treatment effects characterization in terms of decision rules
via an extensive exploration of heterogeneity patterns by an
ensemble-of-trees approach, enforcing high stability in the
discovery. It relies on a two-stage pseudo-outcome regression, and
it is supported by theoretical convergence guarantees. Bargagli-Stoffi,
F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble:
Interpretable Discovery and Inference of Heterogeneous Treatment Effects.
arXiv preprint <doi:10.48550/arXiv.2009.09036>.

Falco Joannes Bargagli Stoffi

Interpretable Discovery and Inference of Heterogeneous Treatment
Effects

Naeem Khoshnevis

Daniela Maria Garcia

Riccardo Cadei

Kwonsang Lee

print.cre function

<dl><dt>x</dt>
<dd>A cre object from running the CRE function.</dd>
<dt>verbose</dt>
<dd>Set level of results description details: 0 for only results
summary, 1 for results and parameters summary, 2 for results and parameters
and rules summary (default 2).</dd>
<dt>...</dt>
<dd>Additional arguments passed to customize the results description.</dd></dl>

Arguments

Extend print function for the CRE object — print.cre

<dl>

<dt>x</dt>
<dd>A cre object from running the CRE function.</dd>


<dt>verbose</dt>
<dd>Set level of results description details: 0 for only results
summary, 1 for results and parameters summary, 2 for results and parameters
and rules summary (default 2).</dd>


<dt>...</dt>
<dd>Additional arguments passed to customize the results description.</dd>

</dl>

print.cre: Extend print function for the CRE object

Description

Usage

Value

Arguments