get_type_distributions

internal

Users can declare causal models over binary nodes, update beliefs about causal types given data, and calculate arbitrary queries. Updating is implemented in 'stan'. See Humphreys and Jacobs, 2023, Integrated Inferences (<DOI: 10.1017/9781316718636>) and Pearl, 2009 Causality (<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_distributions function

<dl><dt>jobs</dt>
<dd>data frame of argument combinations</dd>
<dt>model</dt>
<dd>a list of models</dd>
<dt>n_draws</dt>
<dd>integer specifying number of draws from prior distribution</dd>
<dt>parameters</dt>
<dd>optional list of parameter vectors</dd></dl>

Arguments

helper to get type distributions — get_type_distributions

<dl>

<dt>jobs</dt>
<dd>data frame of argument combinations</dd>


<dt>model</dt>
<dd>a list of models</dd>


<dt>n_draws</dt>
<dd>integer specifying number of draws from prior distribution</dd>


<dt>parameters</dt>
<dd>optional list of parameter vectors</dd>

</dl>

helper to get type distributions

get_type_distributions: helper to get type distributions

Description

Usage

Value

Arguments