E {RobExtremes} | R Documentation |
Generic Function for the Computation of (Conditional) Expectations
Description
Generic function for the computation of (conditional) expectations.
Usage
E(object, fun, cond, ...)
## S4 method for signature 'GEV,missing,missing'
E(object, low = NULL, upp = NULL, ..., diagnostic = FALSE)
## S4 method for signature
## 'DistributionsIntegratingByQuantiles,function,missing'
E(object,
fun, low = NULL, upp = NULL,
rel.tol= getdistrExOption("ErelativeTolerance"),
lowerTruncQuantile = getdistrExOption("ElowerTruncQuantile"),
upperTruncQuantile = getdistrExOption("EupperTruncQuantile"),
IQR.fac = max(1e4,getdistrExOption("IQR.fac")), ..., diagnostic = FALSE)
## S4 method for signature 'Gumbel,missing,missing'
E(object, low = NULL, upp = NULL, ..., diagnostic = FALSE)
## S4 method for signature 'GPareto,missing,missing'
E(object, low = NULL, upp = NULL, ..., diagnostic = FALSE)
## S4 method for signature 'GPareto,function,missing'
E(object, fun, low = NULL, upp = NULL,
rel.tol= getdistrExOption("ErelativeTolerance"),
lowerTruncQuantile = getdistrExOption("ElowerTruncQuantile"),
upperTruncQuantile = getdistrExOption("EupperTruncQuantile"),
IQR.fac = max(1e4,getdistrExOption("IQR.fac")), ..., diagnostic = FALSE)
## S4 method for signature 'Pareto,missing,missing'
E(object, low = NULL, upp = NULL, ..., diagnostic = FALSE)
Arguments
object |
object of class |
fun |
if missing the (conditional) expectation is computed
else the (conditional) expection of |
cond |
if not missing the conditional expectation
given |
rel.tol |
relative tolerance for |
low |
lower bound of integration range. |
upp |
upper bound of integration range. |
lowerTruncQuantile |
lower quantile for quantile based integration range. |
upperTruncQuantile |
upper quantile for quantile based integration range. |
IQR.fac |
factor for scale based integration range (i.e.;
median of the distribution |
... |
additional arguments to |
diagnostic |
logical; if |
Details
The precision of the computations can be controlled via
certain global options; cf. distrExOptions
.
Also note that arguments low
and upp
should be given as
named arguments in order to prevent them to be matched by arguments
fun
or cond
. Also the result, when arguments
low
or upp
is given, is the unconditional value of the
expectation; no conditioning with respect to low <= object <= upp
is done. To be able to use integration after transformation via the
respective probability transformation to [0,1], we introduce a class union
"DistributionsIntegratingByQuantiles"
, which currently comprises
classes "GPareto"
, "Pareto"
, "Weibull"
, "GEV"
.
In addition, the specific method for "GPareto", "function", "missing"
uses integration on [0,1] via the substitution method (y := log(x)).
Diagnostics on the involved integrations are available
if argument diagnostic
is TRUE
. Then there is attribute
diagnostic
attached to the return value, which may be inspected
and accessed through showDiagnostic
and
getDiagnostic
.
Value
The expectation is computed.
Methods
- object = "Gumbel", fun = "missing", cond = "missing":
-
exact evaluation using explicit expressions.
- object = "GPareto", fun = "missing", cond = "missing":
-
exact evaluation using explicit expressions.
- object = "DistributionsIntegratingByQuantiles", fun = "function", cond = "missing":
-
use probability transform, i.e., a substitution
y = p(object)(x)
for numerical integration. - object = "GPareto", fun = "function", cond = "missing":
-
use substitution method (y := log(x)) for numerical integration.
- object = "Pareto", fun = "missing", cond = "missing":
-
exact evaluation using explicit expressions.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de and Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
See Also
distrExIntegrate
, m1df
, m2df
,
Distribution-class
Examples
GP <- GPareto(shape=0.3)
E(GP)
E(GP, fun = function(x){2*x^2}) ## uses the log trafo
P <- Pareto()
E(P)
E(P,fun = function(x){1/(x^2+1)})