| var {distrEx} | R Documentation |
Generic function for the computation of functionals on distributions.
IQR(x, ...) ## S4 method for signature 'UnivariateDistribution': IQR(x) median(x, ...) ## S4 method for signature 'UnivariateDistribution': median(x) mad(x, ...) ## S4 method for signature 'UnivariateDistribution': mad(x) sd(x, ...) ## S4 method for signature 'UnivariateDistribution': sd(x, fun, cond, withCond, useApply, ...) var(x, ...) ## S4 method for signature 'UnivariateDistribution': var(x, fun, cond, withCond, useApply, ...) ## S4 method for signature 'Binom': var(x) ## S4 method for signature 'Beta': var(x) ## S4 method for signature 'Cauchy': var(x) ## S4 method for signature 'Chisq': var(x) ## S4 method for signature 'Dirac': var(x) ## S4 method for signature 'Exp': var(x) ## S4 method for signature 'Fd': var(x) ## S4 method for signature 'Gammad': var(x) ## S4 method for signature 'Geom': var(x) ## S4 method for signature 'Hyper': var(x) ## S4 method for signature 'Logis': var(x) ## S4 method for signature 'Lnorm': var(x) ## S4 method for signature 'Nbinom': var(x) ## S4 method for signature 'Norm': var(x) ## S4 method for signature 'Pois': var(x) ## S4 method for signature 'Td': var(x) ## S4 method for signature 'Unif': var(x) ## S4 method for signature 'Weibull': var(x)
x |
object of class "UnivariateDistribution" |
fun |
if missing the (conditional) variance resp. standard deviation is computed
else the (conditional) variance resp. standard deviation of fun is computed. |
cond |
if not missing the conditional variance resp. standard deviation
given cond is computed. |
... |
additional arguments to fun or E |
useApply |
logical: should sapply, respectively apply
be used to evaluate fund. |
withCond |
logical: is cond in the argument list of fun. |
The value of the corresponding functional at the distribution in the argument is computed.
var, signature(x = "Any"):var — see var.var, signature(x = "UnivariateDistribution"):E()-method.sd, signature(x = "UnivariateDistribution"):E()-method.IQR, signature(x = "Any"):IQR — see IQR.IQR, signature(x = "UnivariateDistribution"):q()-method.median, signature(x = "Any"):median — see median.median, signature(x = "UnivariateDistribution"):q()-method. mad, signature(x = "Any"):mad — see mad.mad, signature(x = "UnivariateDistribution"):q()-method applied to abs(x-median(x)).var, signature(x = "Beta"):var, signature(x = "Binom"):var, signature(x = "Cauchy"):var, signature(x = "Chisq"):var, signature(x = "Dirac"):var, signature(x = "Exp"):var, signature(x = "Fd"):var, signature(x = "Gammad"):var, signature(x = "Geom"):var, signature(x = "Hyper"):var, signature(x = "Logis"):var, signature(x = "Lnorm"):var, signature(x = "Nbinom"):var, signature(x = "Norm"):var, signature(x = "Pois"):var, signature(x = "Td"):var, signature(x = "Unif"):var, signature(x = "Weibull"):Peter Ruckdeschel peter.ruckdeschel@uni-bayreuth.de
distrExIntegrate, m1df, m2df,
Distribution-class,
sd, var, IQR,
median, mad, sd
# Variance of Exp(1) distribution
var(Exp())
#median(Exp())
IQR(Exp())
mad(Exp())
# Variance of N(1,4)^2
var(Norm(mean=1, sd=2), fun = function(x){x^2})
var(Norm(mean=1, sd=2), fun = function(x){x^2}, useApply = FALSE)
## sd -- may equivalently be replaced by var
sd(Pois()) ## uses explicit terms
sd(as(Pois(),"DiscreteDistribution")) ## uses sums
sd(as(Pois(),"UnivariateDistribution")) ## uses simulations
sd(Norm(mean=2), fun = function(x){2*x^2}) ## uses simulations
#
mad(sin(exp(Norm()+2*Pois()))) ## weird