Methods for function validParameter
in package RobExtremes
to check whether a new parameter (e.g. "proposed" by an optimization)
is valid.
validParameter(object, ...)
# S4 method for GParetoFamily
validParameter(object, param, tol=.Machine$double.eps)
# S4 method for WeibullFamily
validParameter(object, param, tol=.Machine$double.eps)
# S4 method for GEVFamily
validParameter(object, param, tol=.Machine$double.eps)
# S4 method for ParetoFamily
validParameter(object, param, tol=.Machine$double.eps)
# S4 method for GEVFamilyMuUnknown
validParameter(object, param,
tol=.Machine$double.eps)
logical
of length 1 --- valid or not
an object of class ParamFamily
either a numeric vector or an object of class
ParamFamParameter
accuracy upto which the conditions have to be fulfilled
additional argument(s) for methods.
method for signature
GParetoFamily
checks if both parameters are finite by is.finite
,
if their length is 1 or 2 (e.g. if one features as nuisance parameter), and if
both are strictly larger than 0 (upto argument tol
)
WeibullFamily
checks if both parameters are finite by is.finite
,
if their length is 1 or 2 (e.g. if one features as nuisance parameter), and if
both are strictly larger than 0 (upto argument tol
)
GEVFamily
checks if both parameters are finite by is.finite
,
if their length is 1 or 2 (e.g. if one features as nuisance parameter), and if
both are strictly larger than 0 (upto argument tol
)
GParetoFamily
checks if both parameters are finite by is.finite
,
if their length is 1 or 2 (e.g. if one features as nuisance parameter), and if
both are strictly larger than 0 (upto argument tol
)
GEVFamilyMuUnknown
checks if all parameters are finite by is.finite
,
if their length is in 1,2,3 (e.g. if one features as nuisance parameter), and scale
and shape both are strictly larger than 0 (upto argument tol
)
G <- GParetoFamily()
validParameter(G, c(scale=0.1, shape=2))
validParameter(G, c(scale=-0.1, shape=-2))
Run the code above in your browser using DataLab