Nothing
cramer.data.frame <- function(x, check = TRUE) {
if (!is.data.frame(x))
stop(deparse(substitute(x)), " is not a data.frame")
x <- as.data.frame(x, stringsAsFactors = TRUE)
if (check) {
# Control and convert the variables to factors
for (k1 in 1:ncol(x)) {
if (!is.factor(x[, k1])){
warning("x[, ", k1, "] is converted to a factor")
x[, k1] = as.factor(x[, k1])
}
}
}
# Compute Cramer's V
assoc <- matrix(nrow = ncol(x), ncol = ncol(x),
dimnames = list(colnames(x), colnames(x)))
for (k1 in 1:ncol(x)) {
x1 <- x[, k1]
assoc[k1, k1] <- CramerV(x1, x1, conf.level = NA)
for (k2 in k1:ncol(x)) {
x2 <- x[, k2]
assoc[k1, k2] <- assoc[k2, k1] <- CramerV(x1, x2, conf.level = NA)
}
}
return(assoc)
}
tschuprow.data.frame <- function(x, check = TRUE) {
if (!is.data.frame(x))
stop(deparse(substitute(x)), " is not a data.frame")
x <- as.data.frame(x, stringsAsFactors = TRUE)
if (check) {
# Control and convert the variables to factors
for (k1 in 1:ncol(x)) {
if (!is.factor(x[, k1])){
warning("x[, ", k1, "] is converted to a factor")
x[, k1] = as.factor(x[, k1])
}
}
}
# Compute Tschuprow's T
assoc <- matrix(nrow = ncol(x), ncol = ncol(x),
dimnames = list(colnames(x), colnames(x)))
for (k1 in 1:ncol(x)) {
x1 <- x[, k1]
assoc[k1, k1] <- TschuprowT(x1, x1)
for (k2 in k1:ncol(x)) {
x2 <- x[, k2]
assoc[k1, k2] <- assoc[k2, k1] <- TschuprowT(x1, x2)
}
}
return(assoc)
}
pearson.data.frame <- function(x, check = TRUE) {
if (!is.data.frame(x))
stop(deparse(substitute(x)), " is not a data.frame")
x <- as.data.frame(x, stringsAsFactors = TRUE)
if (check) {
# Control and convert the variables to factors
for (k1 in 1:ncol(x)) {
if (!is.factor(x[, k1])){
warning("x[, ", k1, "] is converted to a factor")
x[, k1] = as.factor(x[, k1])
}
}
}
# Compute Pearson's contingency coefficient
assoc <- matrix(nrow = ncol(x), ncol = ncol(x),
dimnames = list(colnames(x), colnames(x)))
for (k1 in 1:ncol(x)) {
x1 <- x[, k1]
assoc[k1, k1] <- ContCoef(x1, x1, correct = FALSE)
for (k2 in k1:ncol(x)) {
x2 <- x[, k2]
assoc[k1, k2] <- assoc[k2, k1] <- ContCoef(x1, x2, correct = FALSE)
}
}
return(assoc)
}
phi.data.frame <- function(x, check = TRUE) {
if (!is.data.frame(x))
stop(deparse(substitute(x)), " is not a data.frame")
x <- as.data.frame(x, stringsAsFactors = TRUE)
if (check) {
# Control and convert the variables to factors
for (k1 in 1:ncol(x)) {
if (!is.factor(x[, k1])){
warning("x[, ", k1, "] is converted to a factor")
x[, k1] = as.factor(x[, k1])
}
}
}
# Compute phi
assoc <- matrix(nrow = ncol(x), ncol = ncol(x),
dimnames = list(colnames(x), colnames(x)))
for (k1 in 1:ncol(x)) {
x1 <- x[, k1]
assoc[k1, k1] <- Phi(x1, x1)
for (k2 in k1:ncol(x)) {
x2 <- x[, k2]
assoc[k1, k2] <- assoc[k2, k1] <- Phi(x1, x2)
}
}
return(assoc)
}
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