Combine {sharp} | R Documentation |
Merging stability selection outputs
Description
Merges the outputs from two runs of VariableSelection
,
GraphicalModel
or Clustering
. The two runs must
have been done using the same methods
and the same params
but
with different seed
s. The combined output will contain results based
on iterations from both stability1
and stability2
. This
function can be used for parallelisation.
Usage
Combine(stability1, stability2, include_beta = TRUE)
Arguments
stability1 |
output from a first run of |
stability2 |
output from a second run of
|
include_beta |
logical indicating if the beta coefficients of visited models should be concatenated. Only applicable to variable selection or clustering. |
Value
A single output of the same format.
See Also
VariableSelection
, GraphicalModel
Examples
## Variable selection
# Data simulation
set.seed(1)
simul <- SimulateRegression(n = 100, pk = 50, family = "gaussian")
# Two runs
stab1 <- VariableSelection(xdata = simul$xdata, ydata = simul$ydata, seed = 1, K = 10)
stab2 <- VariableSelection(xdata = simul$xdata, ydata = simul$ydata, seed = 2, K = 10)
# Merging the outputs
stab <- Combine(stability1 = stab1, stability2 = stab2, include_beta = FALSE)
str(stab)
## Graphical modelling
# Data simulation
simul <- SimulateGraphical(pk = 20)
# Two runs
stab1 <- GraphicalModel(xdata = simul$data, seed = 1, K = 10)
stab2 <- GraphicalModel(xdata = simul$data, seed = 2, K = 10)
# Merging the outputs
stab <- Combine(stability1 = stab1, stability2 = stab2)
str(stab)
## Clustering
# Data simulation
simul <- SimulateClustering(n = c(15, 15, 15))
# Two runs
stab1 <- Clustering(xdata = simul$data, seed = 1)
stab2 <- Clustering(xdata = simul$data, seed = 2)
# Merging the outputs
stab <- Combine(stability1 = stab1, stability2 = stab2)
str(stab)
[Package sharp version 1.4.6 Index]