Certificate of exclusion from the selected variables set using SES or MMPC {MXM} | R Documentation |
Certificate of exclusion from the selected variables set using SES or MMPC
Description
Information on why one ore more variables were not selected.
Usage
certificate.of.exclusion(xIndex, sesObject = NULL, mmpcObject = NULL)
certificate.of.exclusion2(xIndex, mmpc2object)
Arguments
xIndex |
A numerical vector with the indices of the predictor variables. |
sesObject |
If you ran SES, wald.ses or perm.ses, give the whole SES object here, otherwise leave it NULL. |
mmpcObject |
If you ran MMPC, wald.mmpc or prm.mmpc, give the whole MMPC object here, otherwise leave it NULL. |
mmpc2object |
If you ran mmpc2, give the whole MMPC object here. |
Value
A list with the conditioning variables (if any), the test statistic and the logarithm of the p-value. In case a variable has been selected a message appears.
Author(s)
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr
See Also
Examples
set.seed(123)
#simulate a dataset with continuous data
dataset <- matrix(runif(100 * 100, 1, 100), ncol = 100)
#define a simulated class variable
target <- 3 * dataset[, 10] + 2 * dataset[, 100] + 3 * dataset[, 20] + rnorm(100, 0, 5)
# define some simulated equivalences
dataset[, 15] <- dataset[, 10] + rnorm(100, 0, 2)
dataset[, 100] <- dataset[, 100] + rnorm(100, 0, 2)
dataset[, 20] <- dataset[, 100] + rnorm(100, 0, 2)
# run the SES algorithm
mod1 <- SES(target, dataset, max_k = 5, threshold = 0.05, test = "testIndFisher",
hash = TRUE, hashObject = NULL);
mod2 <- MMPC(target, dataset, max_k = 5, threshold = 0.05, test = "testIndFisher",
hash = TRUE, hashObject = NULL);
certificate.of.exclusion(c(10, 15, 30, 45, 20), mod1)
certificate.of.exclusion(c(10, 15, 30, 45, 20), NULL, mod2)
[Package MXM version 1.5.5 Index]