Nothing
# # setGeneric("confint",
# # function(object,...){
# # standardGeneric("confint")
# # }
# # )
# #
# # setMethod("confint","MixedTS.qmle",
# # function(object,...){
# # return(a="The function confint is not available for a class of object MixedTS.qmle")
# # }
# # )
# #
# # setGeneric("profile",
# # function(object,...){
# # standardGeneric("profile")
# # }
# # )
# #
# # setMethod("profile","MixedTS.qmle",
# # function(object, ...){
# # return(a="The profile confint is not available for a class of object MixedTS.qmle")
# # }
# # )
#
# # We build a method for the Maximum Likelihood Estimation of The Mixed Tempered Stable.
# # This function use internally the function mle.MixedTS.aux in which if we fix the alpha=2,
# # we get the estimation of the normal variance mean mixture.
# # The function is very flexible since allow us to estimate MixedTS with Gamma mixing
# # density as well as the mixing density specified by the user.
#
# setGeneric("mle.MixedTS",
# function(object,Data=NULL,method="L-BFGS-B", fixed.param=NULL,
# lower.param=NULL,upper.param=NULL,setSup=NULL,setInf=NULL,N=2^10, ...)
# standardGeneric("mle.MixedTS")
# )
#
# setMethod("mle.MixedTS","param.MixedTS",
# function(object,Data=NULL,method="L-BFGS-B", fixed.param=NULL,
# lower.param=NULL,upper.param=NULL,setSup=NULL,setInf=NULL,N=2^10,...){
# call<-match.call()
#
# if(is(object,"MixedTS")){
# if(length(object@Data)>0){
# if(is.null(Data)){
# Data<-object@Data
# }
# }
# }
#
# if(object@Mixing=="Gamma"){
# param0<-list(mu0=object@mu0,mu=object@mu,sigma=object@sigma,a=object@a,
# alpha=object@alpha,lambda_p=object@lambda_p,lambda_m=object@lambda_m)
# res<-mle.MixedTS.aux(data=Data, param0=param0, method,
# fixed.param, lower.param, upper.param,
# MixingDens=object@Mixing, N, MixingLogMGF=NULL,
# paramMixing=NULL,MGFdef=NULL,
# setSup,setInf
# )
# # return(res)
# }else{
# param0<-list(mu0=object@mu0,mu=object@mu,sigma=object@sigma,
# alpha=object@alpha,lambda_p=object@lambda_p,lambda_m=object@lambda_m)
# res<-mle.MixedTS.aux(data=Data, param0=param0, method,
# fixed.param, lower.param, upper.param,
# MixingDens=object@Mixing, N, MixingLogMGF=object@MixingLogMGF,
# paramMixing=object@paramMixing,MGFdef=object@a,
# setSup,setInf
# )
# # dumm<-names(res$time)
# # time<-as.numeric(res$time)
# # names(time)<-dumm
# # result<-new("MixedTS.qmle",time=time,Data=Data,
# # mu0=object@mu0, mu=object@mu,sigma=object@sigma,a=object@a,
# # alpha=object@alpha,lambda_p=object@lambda_p,lambda_m=object@lambda_m,
# # Mixing=object@Mixing, MixingLogMGF=object@MixingLogMGF,
# # paramMixing=object@paramMixing,
# # coef=res$firs.prob$par,
# # fullcoef=res$firs.prob$par,
# # vcov=res$covErr,
# # min=res$firs.prob$value,
# # details=list(),
# # minuslogl=function(){},
# # nobs=length(Data),
# # method=method
# # )
#
# }
#
#
# dumm<-names(res$time)
# time<-as.numeric(res$time)
# names(time)<-dumm
# result<-new("MixedTS.qmle",time=time,Data=Data,
# mu0=object@mu0, mu=object@mu,sigma=object@sigma,a=object@a,
# alpha=object@alpha,lambda_p=object@lambda_p,lambda_m=object@lambda_m,
# Mixing=object@Mixing, MixingLogMGF=object@MixingLogMGF,
# paramMixing=object@paramMixing,
# coef=res$firs.prob$par,
# call=call,
# fullcoef=res$firs.prob$par,
# vcov=res$covErr,
# min=res$firs.prob$value,
# details=res$firs.prob,
# minuslogl=minusloglik.MixedTS,
# nobs=length(Data),
# method=method
# )
#
# return(result)
#
#
# }
# )
setGeneric("summary")
setMethod("summary","MixedTS.qmle",
function(object,...){
cmat <- cbind(Estimate = object@coef, `Std. Error` = sqrt(diag(object@vcov)))
m2logL <- 2 * object@min
new("summary.mle", call=call(quote("Mixed Tempered Stable")), coef = cmat, m2logL = m2logL)
}
)
#
setGeneric("coef")
setMethod("coef","MixedTS.qmle",
function(object,...){
object@coef
}
)
setGeneric("vcov")
setMethod("vcov","MixedTS.qmle",
function(object,...){
object@vcov
}
)
setGeneric("logLik")
setMethod("logLik","MixedTS.qmle",
function(object,...){
if (!missing(...))
warning("extra arguments discarded")
val <- -object@min
if ("nobs" %in% slotNames(object) && !is.na(no <- object@nobs))
attr(val, "nobs") <- no
attr(val, "df") <- length(object@coef)
class(val) <- "logLik"
val
}
)
setGeneric("BIC")
setMethod("BIC","MixedTS.qmle",
function(object,...){
logL <- logLik(object)
npar<-length(object@coef)
nobs <- object@nobs
res<- -2*as.numeric(logL) + npar*log(nobs)
names(res)<-"BIC"
return(res)
}
)
setGeneric("AIC")
setMethod("AIC","MixedTS.qmle",
function(object,...){
logL <- logLik(object)
npar <- length(object@coef)
nobs <- object@nobs
res<-as.numeric(-2*logL + (2*nobs*npar)/(nobs-npar-1))
names(res)<-"AIC"
return(res)
}
)
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