sample.centralmoments {sn} | R Documentation |
Computes sample central moments up to a given order and the first moment from the origin
sample.centralmoments(x, w = rep(1, length(x)), order=4)
x |
a vector of sample values |
w |
an optional vector of weights |
order |
the maximal order of the central moments to be computed; it must be a positive integer (default value 4) |
NA
's are allowed but removed. Averaging of appropriate
quantities is actually performed by weighted.mean
A vector containing the first sample central moments,
in position [2:order]
, and the first moment from the
origin, in the first position of the returned vector
The second component of the returned vector (if order>1
)
gives the sample variance; notice that it differs from the value
returned by var(x)
, since this gives the corrected sample
variance.
Used in conjunction with st.cumulants.inversion
, this
function allows to fit a skew-t distribution by the methods
of moments; see the example below. Note however, that for
stability reasons, this is not adopted as the standard method
for producing initial values of MLE search.
Adelchi Azzalini
st.cumulants.inversion, weighted.mean
data(ais, package='sn') mom <- sample.centralmoments(ais[,"bmi"]) st.cumulants.inversion(cum=c(mom[1:3], mom[4]-3*mom[2]^2)) # parameters of the fitted ST distribution