.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$double.eps^0.3, TruncQuantile = getdistrOption("TruncQuantile"), IQR.fac = 15, ...)
.show.with.sd(est, s)
.getLogDeriv(distr, lowerTruncQuantile = getdistrExOption("ElowerTruncQuantile"), upperTruncQuantile = getdistrExOption("EupperTruncQuantile"), IQR.fac = getdistrExOption("IQR.fac"))
.deleteDim(x)MatrixorFunctionL2ParamFamily --- for
which we want to determine the IC resp. the as. [co]variance of the corresponding
Minimum CvM estimatorParamFamParameter, the parameter value
at which we want to determine the IC resp. the as. [co]variance of the corresponding
Minimum CvM estimatorUnivariateDistribution: integration
measure (resp. distribution) for CvM distancedistrExIntegrate.IQR.fac$*$IQR).preIC
and var or just var; here var is the corresponding
asymptotic variance and preIC the corresponding
EuclRandVarList featuring as argument Curve in ICs of
package RobAStBaseAbscontDistribution.CvMMDCovariance can digest more argumentsdim attributex --- the negative logarithmic
derivative of the densitylogical (length 1)numeric (of length half the input length)logical (length 1)logical (length 1)preIC and var ---see aboveinvisible()x without dim attribute.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 determines the IC resp. the as. [co]variance of
the corresponding Minimum CvM estimator. Still some checking / optimization /
improvement needed.
.show.with.sd is code borrowed from print.fitdistr in
package MASS by B.D. Ripley. It pretty-prints 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.
MLEstimator,
Estimate-class,
MCEstimate-class,
Confint-class,
ParamFamParameter-class