tges: Estimate the restricted Markov equivalence class using Temporal Greedy Equivalence Search

Description

Perform causal discovery using the temporal greedy equivalence search algorithm.

Usage

tges(score, verbose = FALSE)

Value

tges returns a tamat object which is a matrix with a "order" attribute (a character vector listing the temporal order of the variables in the adjacency matrix).

Arguments

score: tiered scoring object to be used. At the moment only scores supported re TemporalBIC and TemporalBDeu.
verbose: indicates whether debug output should be printed.

Author

Tobias Ellegaard Larsen

Examples

Run this code

#Simulate Gaussian data
set.seed(123)
n <- 500
child_x <- rnorm(n)
child_y <- 0.5*child_x + rnorm(n)
child_z <- 2*child_x + child_y  + rnorm(n)

adult_x <- child_x + rnorm(n)
adult_z <- child_z + rnorm(n)
adult_w <- 2*adult_z + rnorm(n)
adult_y <- 2*child_x + adult_w + rnorm(n)

simdata <- data.frame(child_x, child_y, child_z,
                     adult_x, adult_z, adult_w,
                      adult_y)

# Define order in prefix way
prefix_order <- c("child", "adult")

# Define TBIC score
t_score <- new("TemporalBIC", order = prefix_order
               , data = simdata)
# Run tges
tges_pre <- tges(t_score)

# Plot MPDAG
plot(tges_pre)

# Define order in integer way
integer_order <- c(1,1,1,2,2,2,2)

# Define TBIC score
t_score <- new("TemporalBIC", order = integer_order
               , data = simdata)
# Run tges
tges_int <- tges(t_score)

# Plot MPDAG
plot(tges_int)