skewness {modeest} | R Documentation |
The skewness.default
function from package fBasics is completed in order
to implement Bickel's measure of skewness, based on the mode of the
distribution considered.
skewness(x, ...) ## Default S3 method: skewness(x, na.rm = FALSE, method = c("moment", "fisher", "bickel"), M = shorth(x), ...)
x |
numeric. Vector of observations. |
na.rm |
logical. Should missing values be removed? |
method |
character. Specifies the method of computation.
These are either "moment" , "fisher" or "bickel" .
The "moment" method is based on the definition of
skewness for distributions; this form should
be used when resampling (bootstrap or jackknife). The
"fisher" method corresponds to the usual "unbiased"
definition of sample variance, although in the case of skewness
exact unbiasedness is not possible.
|
M |
numeric. (An estimate of) the mode of the observations x .
Default value is shorth(x) . |
... |
arguments to be passed. |
skewness
returns a numeric value.
An attribute which reports the used method is added.
Diethelm Wuertz and other authors for the original skewness
function from
package fBasics;
Paul Poncet paulponcet@yahoo.fr for the slight modification introduced.
015A-BasicStatistics
from package fBasics;
mlv
for general mode estimation;
shorth
for the shorth estimate of the mode;
## Skewness = 0 x <- rnorm(1000) skewness(x, method = "bickel", M = shorth(x)) ## Skewness > 0 (left skewed case) x <- rbeta(1000, 2, 5) skewness(x, method = "bickel", M = betaMode(2, 5)) ## Skewness < 0 (right skewed case) x <- rbeta(1000, 7, 2) skewness(x, method = "bickel", M = hsm(x, bw = 1/3))