To me your answer is opaque (but that seems to be rather a problem of
language ;-) ). Perhaps my question has not been expressed clearly
enough. Let me state it differently:
In the R package e1071 the formulas (implicit) used are (3) and (4) (see
below), the standard deviation used in these
I'm sorry, but my previous message, as often happens, some brackets were
wrong:
Here are the correct formulas:
sd = 1/n * sum((x-mean(x))^2) # (1)
sd = 1/(n-1) * sum((x-mean(x))^2) # (2)
This also occured in the last paragraph.
Dirk
*
Dr.
My last question to the R list is another example of asking too fast
before reading (sorry). But by the way and because it might be
interesting for others, an answer can be found in:
Joanes, D. N. Gill, C. A. (1998) Comparing measures of sample skewness
and kurtosis. Journal of the Royal
This is probably an issue over definitions rather than the correct
answer. To me skewness and kurtosis are functions of the distribution
rather than the population, they are equivalent to expectation rather
than mean. For the normal distribution it makes no sense to estimate
them as the
I wonder whether the functions for skewness and kurtosis in the e1071
package are based on correct formulas.
The functions in the package e1071 are:
#
skewness - function (x, na.rm = FALSE)
{
if (na.rm)
x - x[!is.na(x)]
sum((x -
