With distrExOptions
you can inspect and change
the global variables of the package distrEx.
distrExOptions(...)
distrExoptions(...)
getdistrExOption(x)
distrExOptions()
returns a list of the global variables.
distrExOptions(x)
returns the global variable x.
getdistrExOption(x)
returns the global variable x.
distrExOptions(x=y)
sets the value of the global variable x to y.
any options can be defined, using name = value or by passing a list of such tagged values.
a character string holding an option name.
For compatibility with spelling in package distr, distrExoptions
is
just a synonym to distrExOptions
.
number of Monte-Carlo iterations used for crude
Monte-Carlo integration; defaults to 1e5
.
If integrate
fails and there are
infinite integration limits, the function GLIntegrate
is
called inside of distrExIntegrate
with the corresponding quantiles
GLIntegrateTruncQuantile
respectively,
1 - GLIntegrateTruncQuantile
as finite integration limits; defaults
to 10*.Machine$double.eps
.
The order used for the Gauss-Legendre integration
inside of distrExIntegrate
; defaults to 500.
The lower limit of integration used inside of
E
which corresponds to the ElowerTruncQuantile
-quantile; defaults to
1e-7
.
The upper limit of integration used inside of
E
which corresponds to the (1-ElowerTruncQuantile
)-quantile; defaults to
1e-7
.
The relative tolerance used inside of E
when calling distrExIntegrate
; defaults to .Machine$double.eps^0.25
.
The lower limit of integration used inside
of m1df
which corresponds to the m1dfLowerTruncQuantile
-quantile; defaults to 0.
The relative tolerance used inside of m1df
when calling distrExIntegrate
; defaults to .Machine$double.eps^0.25
.
The lower limit of integration used inside
of m2df
which corresponds to the m2dfLowerTruncQuantile
-quantile;
defaults to 0.
The relative tolerance used inside of m2df
when calling distrExIntegrate
; defaults to .Machine$double.eps^0.25
.
number of support values used for the discretization
of objects of class "AbscontDistribution"
; defaults to 100.
smoothing parameter to smooth objects of class
"DiscreteDistribution"
. This is done via convolution with the
normal distribution Norm(mean = 0, sd = hSmooth)
; defaults to 0.05.
for determining sensible integration ranges, we use
both quantile and scale based methods; for the scale based
method we use the median of the distribution \(\pm\)
IQR.fac
\(\times\) the IQR; defaults to 15.
should names obtained from parameter
coordinates be propagated to return values of specific S4 methods
for functionals; defaults to TRUE
.
Matthias Kohl Matthias.Kohl@stamats.de
distrExOptions()
distrExOptions("ElowerTruncQuantile")
distrExOptions("ElowerTruncQuantile" = 1e-6)
# or
distrExOptions(ElowerTruncQuantile = 1e-6)
getdistrExOption("ElowerTruncQuantile")
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