View source: R/IC_correlation_simplify.R
IC_correlation_simplify | R Documentation |
This function can be used to simplify the network of correlations.
If no vector of variables is given, the variables not linked to any other variable are removed.
If a vector of variables is given, only link to these variables are retained.
https://fr.wikipedia.org/wiki/Iconographie_des_corrélations
IC_correlation_simplify(matrix, variable = NULL)
matrix |
The correlation matrix to simplify |
variable |
a vector with the name of columns to keep |
IC_correlation_simplify simplifies the correlation matrix
A list
Marc Girondot marc.girondot@gmail.com
Lesty, M., 1999. Une nouvelle approche dans le choix des régresseurs de la régression multiple en présence d’interactions et de colinéarités. Revue de Modulad 22, 41-77.
Other Iconography of correlations:
IC_clean_data()
,
IC_threshold_matrix()
,
plot.IconoCorel()
## Not run:
library("HelpersMG")
es <- structure(list(Student = c("e1", "e2", "e3", "e4", "e5", "e6", "e7", "e8"),
Mass = c(52, 59, 55, 58, 66, 62, 63, 69),
Age = c(12, 12.5, 13, 14.5, 15.5, 16, 17, 18),
Assiduity = c(12, 9, 15, 5, 11, 15, 12, 9),
Note = c(5, 5, 9, 5, 13.5, 18, 18, 18)),
row.names = c(NA, -8L), class = "data.frame")
es
df <- IC_clean_data(es, debug = TRUE)
cor_matrix <- IC_threshold_matrix(data=df, threshold = NULL, progress=FALSE)
cor_threshold <- IC_threshold_matrix(data=df, threshold = 0.3)
par(mar=c(1,1,1,1))
set.seed(4)
plot(cor_threshold)
cor_threshold_Note <- IC_correlation_simplify(matrix=cor_threshold, variable="Note")
plot(cor_threshold_Note)
## End(Not run)
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