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.
Matthias Kohl Matthias.Kohl@stamats.de
distrExOptions()
distrExOptions("ElowerTruncQuantile")
distrExOptions("ElowerTruncQuantile" = 1e-6)
# or
distrExOptions(ElowerTruncQuantile = 1e-6)
getdistrExOption("ElowerTruncQuantile")
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