networkVar: Network of correlated variables

In visCorVar: Overlaying of Correlation Circles and Network of Correlated Variables

Description

Network of correlated variables

Usage

networkVar(
  res_compute_mat_similarity,
  names_block_variables,
  names_response_variables,
  cutoff = 0
)

Arguments

res_compute_mat_similarity	res_compute_mat_similarity is the output of the function computeMatSimilarity
names_block_variables	type : character vector. names_block_variables contains the names of selected block variables.
names_response_variables	type : charcater vector. names_response_variables contains the names of the response variables which will be in the network.
cutoff	type : numeric. If the similarity between two selected block variables is larger than cutoff in absolute value, these variable will be in the network.

Details

The function networkVar create a network of correlated variables. The variables of interest and the response variables will be in the network. If the similarity between two selected block variables is larger than cutoff in absolute value, these variable will be in the network.

Value

a list containing

• gR type : igraph graph. This object contains all the information needed to create a network. This object can be exported in graphml format.

• cutoff type : numeric. An input parameter of the function networkVar.

Examples

library(RColorBrewer)
load(system.file("extdata", "res_data_integration.rda", package="visCorVar"))
load(system.file("extdata", "block_Y.rda", package="visCorVar"))
load(system.file("extdata", "var_interest.rda", package="visCorVar"))
comp = 1:2
cutoff_comp = 0.8
res_matCorAddVar = matCorAddVar(res_data_integration, block_Y,
 cutoff_comp, var_interest, comp)
list_cor_comp_selected_var_resp_var = res_matCorAddVar$list_cor_comp_selected_var_resp_var
list_vec_index_block_select = res_matCorAddVar$list_vec_index_block_select
mat_cor_comp1 = res_matCorAddVar$mat_cor_comp1
mat_cor_comp2 = res_matCorAddVar$mat_cor_comp2
res_compute_mat_similarity = computeMatSimilarity(res_matCorAddVar)
names_blocks = c("X1", "X3")
names_response_variables = c("A", "B")
comp = 1:2
names_block_variables = circleCor(list_cor_comp_selected_var_resp_var, list_vec_index_block_select,
  mat_cor_comp1, mat_cor_comp2, names_blocks, names_response_variables, comp, 0.85, -1,
   1, -1, 1, colorRampPalette(brewer.pal(9, "Spectral"))(dim(mat_cor_comp1)[1] + 1), rad.in = 0.5, 
   0.7, 0.8, c(1.2, 0), 20)
names_resp_var2 = c("A")
res_networkVar = networkVar(res_compute_mat_similarity, names_block_variables, names_resp_var2,
  0)

visCorVar documentation built on Sept. 6, 2020, 3:01 a.m.