These functions are used internally by package “distrMod”.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  .inArgs(arg, fct)
.isUnitMatrix(m)
.csimpsum(fx)
.validTrafo(trafo, dimension, dimensionwithN)
.CvMMDCovariance(L2Fam, param, mu = distribution(L2Fam),
withplot = FALSE, withpreIC = FALSE,
N = getdistrOption("DefaultNrGridPoints")+1,
rel.tol=.Machine$double.eps^0.3,
TruncQuantile = getdistrOption("TruncQuantile"),
IQR.fac = 15, ...)
.show.with.sd(est, s)
.getLogDeriv(distr,
lowerTruncQuantile = getdistrExOption("ElowerTruncQuantile"),
upperTruncQuantile = getdistrExOption("EupperTruncQuantile"),
IQR.fac = getdistrExOption("IQR.fac"))
.deleteDim(x)

arg 
a formal argument as character 
fct 
a function 
m 
a matrix 
est 
an estimator; usually a vector 
s 
a standard deviation 
trafo 
an object of class 
dimension 
a numeric — length of main part of the parameter 
dimensionwithN 
a numeric — length of main and nuisance part of the parameter 
L2Fam 
an object of class 
mu 
an object of class 
withplot 
logical; defaults to 
withpreIC 
logical: shall we return a list with components 
... 
currently not used 
N 
integer; the number of grid points at which to evaluate the antiderivative in case of an absolutely continuous distribution; more precisely, internally this becomes 2N+1 
rel.tol 
relative tolerance for 
TruncQuantile 
numeric in (0,1); in case of an unbounded support of the distribution the quantile level at which to cut the distribution 
IQR.fac 
a positive numeric; a factor by which to multiply the IQR of the distribution to obtain a sensible cut of point for the integration bounds 
lowerTruncQuantile 
lower quantile for quantile based integration range. 
upperTruncQuantile 
upper quantile for quantile based integration range. 
fx 
a vector of function evaluations multiplied by the gridwidth 
distr 
an object of class 
... 
further argument to be passed through — so

x 
a possibly named vector, which may have a 
.inArgs
(borrowed from package distr)
checks whether an argument arg
is a formal argument of
fct
— not vectorized.
.csimpsum
(borrowed from package distr)
produces a primitimive function out of function evaluations by means
of vectorized Simpson quadrature method, returning already the function values
of the prime function on a grid; it is to mimick the behaviour
of cumsum
.
.isUnitMatrix
checks whether the argument is a unit matrix.
.validTrafo
checks whether the argument is a valid transformation.
.CvMMDCovariance
computes the asymptotic covariance of the CvMMDE
according to H. Rieder (1994) "Robust Asymptotic Statistics".
.show.with.sd
is code borrowed from print.fitdistr
in
package MASS by B.D. Ripley. It prettyprints estimates with corresponding
sd's below.
.getLogDeriv
determines numerically the negative logarithmic derivative of the
density of distribution distr
; to this end uses D1ss
,
D2ss
from Martin Maechler's package sfsmisc.
.deleteDim
deletes a possible dim
argument (sets it to NULL
)
but retains all other possible attributes, in particular a name
attribute.
.getLogderiv 
a function in one argument 
.inArgs 

.csimpsum 

.isUnitMatrix 

.validTrafo 

.CvMMDCovariance 
corresponding as. [co]variance of
the corresponding Minimum CvM estimator or list withcomponents

.show.with.sd 

.deleteDim 
vector 
.CvMMDCovariance 
if argument 
Peter Ruckdeschel peter.ruckdeschel@unioldenburg.de Matthias Kohl Matthias.Kohl@stamats.de
MLEstimator
,
Estimateclass
,
MCEstimateclass
,
Confintclass
,
ParamFamParameterclass
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.