| summary.SECdistr {sn} | R Documentation |
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.
## S4 method for signature 'SECdistrUv' summary(object, cp.type = "auto", probs) ## S4 method for signature 'SECdistrMv' summary(object, cp.type = "auto")
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 non-parametric 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
SECdistrUv-class and SECdistrMv-class objects
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 # quantile-based 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="ESN-2d")
summary(esn2)