get_type_prob

Gets probability of vector of causal types given a single
realization of parameters, possibly drawn from model priors.

Users can declare binary causal models, update beliefs about causal types given data and calculate arbitrary estimands. Model definition makes use of 'dagitty' functionality. Updating is implemented in 'stan'. The approach used in 'CausalQueries' is a generalization of the 'biqq' models described in "Mixing Methods: A Bayesian Approach" (Humphreys and Jacobs, 2015, <DOI:10.1017/S0003055415000453>). The conceptual extension makes use of work on probabilistic causal models described in Pearl's Causality (Pearl, 2009, <DOI:10.1017/CBO9780511803161>).

Till Tietz

CausalQueries

Make, Update, and Query Binary Causal Models

Clara Bicalho

Jasper Cooper

Macartan Humphreys

Alan Jacobs

Merlin Heidemanns

Lily Medina

Julio Solis

Georgiy Syunyaev

get_type_prob function

<dl><dt>model</dt>
<dd>A <code>causal_model</code>. A model object generated by
<code>make_model</code>.</dd>
<dt>P</dt>
<dd>A <code>data.frame</code>. Parameter matrix. Not required but may be
provided to avoid repeated computation for simulations.</dd>
<dt>parameters</dt>
<dd>A vector of real numbers in [0,1]. Values of parameters to
specify (optional). By default, parameters is drawn from
<code>model$parameters_df</code>.</dd></dl>

Arguments

Get type probabilities — get_type_prob

<dl>

<dt>model</dt>
<dd>A <code>causal_model</code>. A model object generated by
<code>make_model</code>.</dd>


<dt>P</dt>
<dd>A <code>data.frame</code>. Parameter matrix. Not required but may be
provided to avoid repeated computation for simulations.</dd>


<dt>parameters</dt>
<dd>A vector of real numbers in [0,1]. Values of parameters to
specify (optional). By default, parameters is drawn from
<code>model$parameters_df</code>.</dd>

</dl>

Get type probabilities

get_type_prob: Get type probabilities

Description

Usage

Value

Arguments

Details