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local({
## Prepare
require(outliers)
## Compute
vars <- rk.list (women[["weight"]], women[["height"]])
results <- data.frame ("Variable Name"=I(names (vars)), check.names=FALSE)
for (i in 1:length (vars)) {
var <- vars[[i]]
results[i, 'Length'] <- length (var)
results[i, 'NAs'] <- sum (is.na(var))
var <- na.omit (var) # omit NAs for all further calculations
results[i, "Error"] <- tryCatch ({
# This is the core of the calculation
t <- dixon.test (var, type = 0, opposite = FALSE, two.sided = TRUE)
results[i, "Dixon Q-statistic"] <- t$statistic["Q"]
results[i, "p-value"] <- t$p.value
results[i, "Alternative Hypothesis"]<- rk.describe.alternative (t)
results[i, "Mean"] <- mean (var)
results[i, "Standard Deviation"] <- sd (var)
results[i, "Median"] <- median (var)
results[i, "Minimum"] <- min (var)
results[i, "Maximum"] <- max (var)
NA # no error
}, error=function (e) e$message) # catch any errors
}
if (all (is.na (results$"Error"))) results$"Error" <- NULL
## Print result
rk.header ("Dixon test for outlier", parameters=list("Variant of test"="0 (Automatic)",
"Opposite"="no",
"two-sided"="yes"))
rk.results (results)
})
local({
## Prepare
require(outliers)
## Compute
vars <- rk.list (women[["weight"]], women[["height"]])
results <- data.frame ("Variable Name"=I(names (vars)), check.names=FALSE)
for (i in 1:length (vars)) {
var <- na.omit (vars[[i]])
results[i, "Error"] <- tryCatch ({
# This is the core of the calculation
t <- dixon.test (var, type = 0, opposite = TRUE, two.sided = FALSE)
results[i, "Dixon Q-statistic"] <- t$statistic["Q"]
results[i, "p-value"] <- t$p.value
results[i, "Alternative Hypothesis"]<- rk.describe.alternative (t)
NA # no error
}, error=function (e) e$message) # catch any errors
}
if (all (is.na (results$"Error"))) results$"Error" <- NULL
## Print result
rk.header ("Dixon test for outlier", parameters=list("Variant of test"="0 (Automatic)",
"Opposite"="yes",
"two-sided"="no"))
rk.results (results)
})
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