Produce a summary of an object of class either
"SECdistrUv"
or "SECdistrMv"
, which refer to a univariate or a
multivariate SEC distribution, respectively. Both types of
objects can be produced by makeSECditr
.
1 2 3 4 5 
object 
an object of class 
cp.type 
a character string to select the required variance of
CP parameterization; possible values are 
probs 
in the univariate case, a vector of probabilities for which
the corresponding quantiles are required. If missing, the vector

A list with the following components:
family 
name of the family within the SEC class, character 
dp 
DP parameters, a list or a vector 
name 
the name of the distribution, character string 
compNames 
in the multivariate case the names of the components, a character vector 
cp 
CP parameters, a list or a vector 
cp.type 
the name of the selected variant of the CP set 
aux 
a list with auxiliary ingredients (mode, coefficients of skewness and kurtosis, in the parametric and nonparametric variants, and more). 
DP and CP are vectors if class(object)
is
SECdistrUv
(univariate distribution); they are lists if codeclass(object) is SECdistrMv
(multivariate distribution).
The examples below show how extract components from aux
and other slots.
Adelchi Azzalini
makeSECdistr
for extracting a SEC
distribution from a selm
fit
methods mean
and vcov
for computing the mean (vector) and the variance (matrix) of
SECdistrUvclass
and SECdistrMvclass
objects
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  f3 < makeSECdistr(dp=c(3,2,5), family="SC")
summary(f3)
s < summary(f3, probs=(1:9)/10)
print(slotNames(s))
print(names(slot(s,"aux"))) # the components of the 'aux' slot
slot(s, "aux")$mode # the same of modeSECdistr(object=f3)
slot(s, "aux")$q.measures # quantilebased measures of skewness and kurtosis
#
dp3 < list(xi=1:3, Omega=toeplitz(1/(1:3)), alpha=c(3, 8, 5), nu=6)
st3 < makeSECdistr(dp=dp3, family="ST", compNames=c("U", "V", "W"))
s < summary(st3)
dp < slot(s, "dp") # the same of slot(st3, "dp")
slot(s, "cp")$var.cov # the same of vcov(st3)
slot(s, "aux")$delta.star # comprehensive coefficient of shape
slot(s, "aux")$mardia # Mardia's measures of asymmetry and kurtosis
#
dp2 < list(xi=rep(0,2), Omega=matrix(c(2,2,2,4),2,2), alpha=c(3,5), tau=1)
esn2 < makeSECdistr(dp=dp2, family="ESN", name="ESN2d")
summary(esn2)

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