Hello,
In certain cases fligner.test() returns NaN statistic and NA p-value.
The issue happens when, after centering with the median, all absolute values
become constant, which ten leads to identical ranks.
Below are a few examples:
# 2 groups, 2 values each
# issue is caused by residual values after centering (-0.5, 0.5, -0.5, 0.5)
# then, after taking the absolute value, all the ranks become identical.
> fligner.test(c(2,3,4,5), gl(2,2))
Fligner-Killeen test of homogeneity of variances
data: c(2, 3, 4, 5) and gl(2, 2)
Fligner-Killeen:med chi-squared = NaN, df = 1, p-value = NA
# similar situation with more observations and 3 groups
> fligner.test(c(2,3,2,3,4,4,5,5,8,9,9,8), gl(3,4))
Fligner-Killeen test of homogeneity of variances
data: c(2, 3, 2, 3, 4, 4, 5, 5, 8, 9, 9, 8) and gl(3, 4)
Fligner-Killeen:med chi-squared = NaN, df = 2, p-value = NA
Two simple patches are proposed below. One returns an error, and another
returns a p-value of 1.
Not sure which one is more appropriate, so submitting both.
Warm regards,
Karolis Koncevičius
---
Index: fligner.test.R
===================================================================
--- fligner.test.R (revision 79650)
+++ fligner.test.R (working copy)
@@ -59,8 +59,13 @@
stop("data are essentially constant")
a <- qnorm((1 + rank(abs(x)) / (n + 1)) / 2)
- STATISTIC <- sum(tapply(a, g, "sum")^2 / tapply(a, g, "length"))
- STATISTIC <- (STATISTIC - n * mean(a)^2) / var(a)
+ if (var(a) > 0) {
+ STATISTIC <- sum(tapply(a, g, "sum")^2 / tapply(a, g, "length"))
+ STATISTIC <- (STATISTIC - n * mean(a)^2) / var(a)
+ }
+ else {
+ STATISTIC <- 0
+ }
PARAMETER <- k - 1
PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
names(STATISTIC) <- "Fligner-Killeen:med chi-squared”
---
Index: fligner.test.R
===================================================================
--- fligner.test.R (revision 79650)
+++ fligner.test.R (working copy)
@@ -57,6 +57,8 @@
x <- x - tapply(x,g,median)[g]
if (all(x == 0))
stop("data are essentially constant")
+ if (var(abs(x)) == 0)
+ stop("absolute residuals from the median are essentially constant")
a <- qnorm((1 + rank(abs(x)) / (n + 1)) / 2)
STATISTIC <- sum(tapply(a, g, "sum")^2 / tapply(a, g, "length"))
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