set_sampling_args

set_sampling_args
From 'rstanarm' (November 1st, 2019)

internal

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

set_sampling_args function

<dl><dt>object</dt>
<dd>A <code>stanfit</code> object.</dd>
<dt>user_dots</dt>
<dd>A list. User commands.</dd>
<dt>user_adapt_delta</dt>
<dd>A double between 0 and 1.
Adapt delta passed by the user</dd>
<dt>...</dt>
<dd>further arguments to be passed to 'stan'</dd></dl>

Arguments

set_sampling_args
From 'rstanarm' (November 1st, 2019) — set_sampling_args

<dl>

<dt>object</dt>
<dd>A <code>stanfit</code> object.</dd>


<dt>user_dots</dt>
<dd>A list. User commands.</dd>


<dt>user_adapt_delta</dt>
<dd>A double between 0 and 1.
Adapt delta passed by the user</dd>


<dt>...</dt>
<dd>further arguments to be passed to 'stan'</dd>

</dl>

set_sampling_args
From 'rstanarm' (November 1st, 2019)

set_sampling_args: set_sampling_args From 'rstanarm' (November 1st, 2019)

Description

Usage

Value

Arguments

Details