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causalDisco (version 1.0.1)

CausalDiscoSearch: R6 Interface to causalDisco Search Algorithms

Description

This class implements the search algorithms from the causalDisco package, which wraps and adds temporal order to pcalg algorithms. It allows to set the data, sufficient statistics, test, score, and algorithm.

Arguments

Public fields

data

A data.frame holding the data set currently attached to the search object. Can be set with set_data().

score

A function that will be used to build the score, when data is set. Can be set with $set_score(). Recognized values are:

  • "tbic" - Temporal BIC score for Gaussian data. See TemporalBIC.

  • "tbdeu" - Temporal BDeu score for discrete data. See TemporalBDeu.

test

A function that will be used to test independence. Can be set with $set_test(). Recognized values are:

  • "reg" - Regression test for discrete or binary data. See reg_test().

  • "fisher_z" - Fisher Z test for Gaussian data. See cor_test().

alg

A function that will be used to run the search algorithm. Can be set with $set_alg(). Recognized values are:

  • "tfci" - TFCI algorithm. See tfci().

  • "tges" - TGES algorithm. See tges().

  • "tpc" - TPC algorithm. See tpc().

params

A list of parameters for the test and algorithm. Can be set with $set_params(). TODO: not secure yet in terms of distributing arguments. Use with caution.

suff_stat

Sufficient statistic. The format and contents of the sufficient statistic depends on which test is being used.

knowledge

A Knowledge object holding background knowledge.

Methods

Method new()

Constructor for the CausalDiscoSearch class.

Usage

CausalDiscoSearch$new()

Method set_params()

Sets the parameters for the test and algorithm.

Usage

CausalDiscoSearch$set_params(params)

Arguments

params

A list of parameters to set.

Method set_data()

Sets the data for the search algorithm.

Usage

CausalDiscoSearch$set_data(data, set_suff_stat = TRUE)

Arguments

data

A data.frame or a matrix containing the data.

set_suff_stat

Logical; whether to set the sufficient statistic.

Method set_suff_stat()

Sets the sufficient statistic for the data.

Usage

CausalDiscoSearch$set_suff_stat()

Method set_test()

Sets the test for the search algorithm.

Usage

CausalDiscoSearch$set_test(method, alpha = 0.05)

Arguments

method

A string specifying the type of test to use.

alpha

Significance level for the test.

Method set_score()

Sets the score for the search algorithm.

Usage

CausalDiscoSearch$set_score(method, params = list())

Arguments

method

A string specifying the type of score to use.

params

A list of parameters to pass to the score function.

Method set_alg()

Sets the algorithm for the search.

Usage

CausalDiscoSearch$set_alg(method)

Arguments

method

A string specifying the type of algorithm to use.

Method set_knowledge()

Sets the background knowledge for the search with a Knowledge object.

Usage

CausalDiscoSearch$set_knowledge(kn, directed_as_undirected = FALSE)

Arguments

kn

A Knowledge object.

directed_as_undirected

Logical; whether to treat directed edges in the knowledge as undirected. Default is FALSE. This is due to the nature of how pcalg handles background knowledge when using pcalg::skeleton() under the hood in tpc() and tfci().

Method run_search()

Runs the search algorithm on the data.

Usage

CausalDiscoSearch$run_search(data = NULL, set_suff_stat = TRUE)

Arguments

data

A data.frame or a matrix containing the data.

set_suff_stat

Logical; whether to set the sufficient statistic

Method clone()

The objects of this class are cloneable with this method.

Usage

CausalDiscoSearch$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

knowledge().

Examples

Run this code
# Generally, we do not recommend using the R6 classes directly, but rather
# use the disco() or any method function, for example pc(), instead.

data(tpc_example)

# background knowledge (tiers + one exogenous var)
kn <- knowledge(
  tpc_example,
  tier(
    child ~ starts_with("child"),
    youth ~ starts_with("youth"),
    old ~ starts_with("oldage")
  )
)

# Recommended (TPC example):
my_tpc <- tpc(engine = "causalDisco", test = "fisher_z", alpha = 0.05)
result <- disco(data = tpc_example, method = my_tpc, knowledge = kn)
plot(result)

# or
my_tpc <- my_tpc |>
  set_knowledge(kn)
result <- my_tpc(tpc_example)
plot(result)

# Using R6 class:

# --- Constraint-based: TPC ----------------------------------------------------
s_tpc <- CausalDiscoSearch$new()
s_tpc$set_params(list(verbose = FALSE))
s_tpc$set_test("fisher_z", alpha = 0.2)
s_tpc$set_alg("tpc")
s_tpc$set_knowledge(kn, directed_as_undirected = TRUE)
s_tpc$set_data(tpc_example)
res_tpc <- s_tpc$run_search()
print(res_tpc)

# Switch to TFCI on the same object (reuses suffStat/test)
s_tpc$set_alg("tfci")
res_tfci <- s_tpc$run_search()
print(res_tfci)

# --- Score-based: TGES --------------------------------------------------------
s_tges <- CausalDiscoSearch$new()
s_tges$set_score("tbic") # Gaussian temporal score
s_tges$set_alg("tges")
s_tges$set_data(tpc_example, set_suff_stat = FALSE) # suff stat not used for TGES
s_tges$set_knowledge(kn)
res_tges <- s_tges$run_search()
print(res_tges)

# --- Intentional error demonstrations ----------------------------------------

# run_search() without setting an algorithm
try(CausalDiscoSearch$new()$run_search(tpc_example))

# set_suff_stat() requires data and test first
s_err <- CausalDiscoSearch$new()
try(s_err$set_suff_stat()) # no data & no test
s_err$set_data(tpc_example, set_suff_stat = FALSE)
try(s_err$set_suff_stat()) # no test

# unknown test / score / algorithm
try(CausalDiscoSearch$new()$set_test("not_a_test"))
try(CausalDiscoSearch$new()$set_score("not_a_score"))
try(CausalDiscoSearch$new()$set_alg("not_an_alg"))

# set_knowledge() requires a `knowledge` object
try(CausalDiscoSearch$new()$set_knowledge(list(not = "Knowledge")))

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