micd (version 1.1.1)

boot.graph: Bootstrap Resampling for the PC-MI- and the FCI-MI-algorithm

Description

Generate R bootstrap replicates for the PC or FCI algorithm for data with missing values.

Usage

boot.graph(
  data,
  select = NULL,
  method = c("pcMI", "fciMI"),
  method.mice = NULL,
  args,
  R,
  m = 10,
  args.residuals = NULL,
  seed = NA,
  quickpred = FALSE,
  ...
)

Value

List of objects of class pcalgo (see pcalg::pcAlgo) or of fcmialgo (see pcalg::fciAlgo).

Arguments

data

Data.frame with missing values

select

Variable of integers, indicating columns to select from a data frame; only continuous variables can be included in the model selection

method

Character string specifying the algorithm for causal discovery from the package 'pcalg'.

method.mice

Character string specifying imputation method; see mice::mice() for more information.

args

Arguments passed to method. NOTE: argument labels is set internally and should not be used!

R

A positive integer number of bootstrap replications.

m

Number of chains included in mice()`.

args.residuals

(Optional) list containing vertices and confounders. May be specified when residuals for vertices should be calculated in each bootstrap data set. See makeResiduals() for more information

seed

A positive integer that is used as argument for set.seed().

quickpred

If true, mice uses quickpred to select predictors.

...

Further arguments passed to the imputation function mice().

Examples

data(windspeed)
daten <- mice::ampute(windspeed)$amp

# \donttest{
bgraph <- boot.graph(data = daten,
                     method = "pcMI",
                     args = "solve.confl = TRUE, alpha = 0.05",
                     R = 5)
# }