make_prior_distribution

Create a `n_param`x `n_draws` database of possible lambda draws to be
attached to the model.

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

make_prior_distribution function

<dl><dt>model</dt>
<dd>A <code>causal_model</code>. A model object generated by
<code>make_model</code>.</dd>
<dt>n_draws</dt>
<dd>A scalar. Number of draws.</dd></dl>

Arguments

Make a prior distribution from priors — make_prior_distribution

<dl>

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


<dt>n_draws</dt>
<dd>A scalar. Number of draws.</dd>

</dl>

Make a prior distribution from priors

make_prior_distribution: Make a prior distribution from priors

Description

Usage

Value

Arguments

Examples