plotStability {stablespec}

Plot of edge and causal path stability.

Description

Plot each of the stability of causal path and edge including the threshold of stability and model complexity.

Usage

plotStability(listOfFronts = NULL, threshold = NULL, stableCausal = NULL,
  stableCausal_l1 = NULL, stableEdge = NULL, longitudinal = NULL)

Arguments

listOfFronts

list of models including their fitness and subset index.

threshold

threshold of stability selection. The default is 0.6.

stableCausal

list of causal path stability for the whole range of model complexities.

stableCausal_l1

list of causal path stability of length 1 for the whole range of model complexities.

stableEdge

list of edge stability for the whole range of model complexities.

longitudinal

TRUE for longitudinal data, and FALSE cross-sectional data.

Value

Plot of causal path and edge stability for every pair of variables, including plots of all edge stabilites and all cauasl path stabilities.

Author(s)

Ridho Rahmadi [e-mail]

Examples

the_data <- crossdata6V
numSubset <- 1
num_iteration <- 5
num_pop <- 10
mut_rate <- 0.075
cross_rate <- 0.85
longi <- FALSE
num_time <- 1
the_co <- "covariance"
#assummed that variable 5 does not cause variables 1, 2, and 3
cons_matrix <- matrix(c(5, 1, 5, 2, 5, 3), 3, 2, byrow=TRUE)
th <- 0.1
to_plot <- FALSE

result <- stableSpec(theData=the_data, nSubset=numSubset,
iteration=num_iteration,
nPop=num_pop, mutRate=mut_rate, crossRate=cross_rate,
longitudinal=longi, numTime=num_time,
co=the_co, consMatrix=cons_matrix, threshold=th, toPlot=to_plot)

plotStability(listOfFronts=result$listOfFronts, threshold=th,
stableCausal=result$causalStab,
stableCausal_l1=result$causalStab_l1,
stableEdge=result$edgeStab,
longitudinal=longi)