sampler.net.attr.generator: Single Component Sampler Settings (R6 Class)

In iglm: Regression under Interference in Connected Populations

Single Component Sampler Settings (R6 Class)

Description

The 'sampler_net_attr' class is a simple R6 container used within the 'sampler.iglm' class. It holds the MCMC sampling parameters for a single component of the 'iglm' model, such as one attribute (e.g., 'x_attribute') or a part of the network (e.g., 'z_network' within the overlap). It stores the number of proposals and the TNT flag. The random seed is managed centrally by the parent 'sampler.iglm' object.

Active bindings

n_proposals

('integer') Read-only. Number of MCMC proposals per step.

tnt

('logical') Read-only. Whether TNT sampling is used.

Methods

Public methods

• sampler.net.attr.generator$new()

• sampler.net.attr.generator$print()

• sampler.net.attr.generator$gather()

• sampler.net.attr.generator$set_n_proposals()

• sampler.net.attr.generator$set_tnt()

• sampler.net.attr.generator$save()

• sampler.net.attr.generator$clone()

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Method new()

Create a new 'sampler_net_attr' object.

Usage

sampler.net.attr.generator$new(n_proposals = 10000, file = NULL, tnt = TRUE)

Arguments

n_proposals

(integer) The number of MCMC proposals (iterations) to perform for this specific component during each sampling step. Default is 10000. Must be a non-negative integer.

file

(character or 'NULL') If provided, loads the sampler state from the specified .rds file instead of initializing from parameters.

tnt

(logical) If 'TRUE' (default), use Tie-No-Tie sampling (only if used for networks).

Returns

A new 'sampler_net_attr' object.

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Method print()

Print a summary of the sampler settings for this component.

Usage

sampler.net.attr.generator$print(indent = "  ")

Arguments

indent

(character) Indentation string. Default is " ".

Returns

The object itself, invisibly.

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Method gather()

Gathers all data into a list.

Usage

sampler.net.attr.generator$gather()

Returns

A list with 'n_proposals' and 'tnt'.

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Method set_n_proposals()

Sets the number of MCMC proposals.

Usage

sampler.net.attr.generator$set_n_proposals(n_proposals)

Arguments

n_proposals

(integer) Number of proposals.

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Method set_tnt()

Sets whether to use TNT sampling.

Usage

sampler.net.attr.generator$set_tnt(tnt)

Arguments

tnt

(logical) 'TRUE' to use TNT sampling.

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Method save()

Save state to an .rds file.

Usage

sampler.net.attr.generator$save(file)

Arguments

file

(character) File path.

Returns

The object itself, invisibly.

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Method clone()

The objects of this class are cloneable with this method.

Usage

sampler.net.attr.generator$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

iglm documentation built on April 23, 2026, 5:07 p.m.