Nothing
## ----------------------------------- estimation parameters -------------------------
theta <<- c(1.45,0.55,1,0)
pm <<- 0
set.seed(2345);x <<- rstable(1000,theta[1],theta[2],theta[3],theta[4],pm)
theta0 <<- c(1.35,0.45,1,0)
##------------------------------------ Kout ------------------------------------------
example.Kout <- function(){
objKout <- Estim(EstimMethod="Kout",data=x,
ComputeCov=FALSE,HandleError=FALSE,
spacing="Kout")
objKoutUniform <- Estim(EstimMethod="Kout",data=x,
ComputeCov=FALSE,HandleError=FALSE,
spacing="ArithSpac",nb_t=23)
objKoutArith <- Estim(EstimMethod="Kout",data=x,
ComputeCov=FALSE,HandleError=FALSE,
spacing="UniformSpac",nb_u=13)
objKoutFree <- Estim(EstimMethod="Kout",data=x,
ComputeCov=FALSE,HandleError=FALSE,
spacing="free",t_points=seq(0.2,2.5,length.out=12),
u_points=seq(0.1,1.85,length.out=10))
list(kout=objKout,
Uniform=objKoutUniform,
Arith=objKoutArith,
Free=objKoutFree
)
}
##------------------------------------ Cgmm ------------------------------------------
example.Cgmm <- function(index=1){
subdivisions=50
alphaReg=0.01
randomIntegrationLaw="unif"
IntegrationMethod="Simpson"
if (index==1){ ## Takes around 12 min
obj2SCgmm <- Estim(EstimMethod="Cgmm",data=x,
ComputeCov=TRUE,HandleError=FALSE,
type="2S",alphaReg=alphaReg,
subdivisions=subdivisions,
IntegrationMethod=IntegrationMethod,
randomIntegrationLaw=randomIntegrationLaw,s_min=0,s_max=1,
theta0=NULL,pm=pm,PrintTime=FALSE,level=0.95)
objITCgmm <- NULL; objCueCgmm <- NULL
}
else {
IterationControl <- list(NbIter=3,PrintIter=FALSE,RelativeErrMax=1e-2)
randomIntegrationLaw="norm"
IntegrationMethod="Uniform"
if (index==2){ # takes 6 min
objITCgmm <- Estim(EstimMethod="Cgmm",data=x,
ComputeCov=TRUE,HandleError=FALSE,
type="IT",alphaReg=alphaReg,
subdivisions=subdivisions,
IntegrationMethod=IntegrationMethod,
randomIntegrationLaw=randomIntegrationLaw,s_min=0,s_max=1,
theta0=theta0,IterationControl=IterationControl,pm=pm,
PrintTime=FALSE,level=0.92,mu=0.5,sigma=2) # mu and sigma: params of the normal law
obj2SCgmm <- NULL ;objCueCgmm <- NULL
}
else { #takes 17 min
objCueCgmm <- Estim(EstimMethod="Cgmm",data=x,
ComputeCov=TRUE,HandleError=FALSE,
type="Cue",alphaReg=alphaReg,
subdivisions=subdivisions,
IntegrationMethod=IntegrationMethod,
randomIntegrationLaw=randomIntegrationLaw,s_min=0,s_max=1,
theta0=theta0,IterationControl=IterationControl,pm=pm,
PrintTime=FALSE,level=0.92)
obj2SCgmm <- NULL ;objITCgmm <- NULL
}
}
list(twoStep=obj2SCgmm,
IT=objITCgmm,
Cue=objCueCgmm)
}
##------------------------------------ ML ------------------------------------------
example.ML <- function(){# takes 4min
Estim(EstimMethod="ML",data=x,theta0=NULL,ComputeCov=TRUE,HandleError=FALSE,
level=0.90,subdivisions=50,pm=0)
}
##----------------------------------- GMM ------------------------------------------
example.GMM.Classic <- function(){ #takes less than 1 min
## free
t_scheme="free"
algo <- "2SGMM"
alphaReg=0.005
regularization="Tikhonov"
WeightingMatrix="DataVar"
t_seq=seq(0.1,2,length.out=42)
objfree <- Estim(EstimMethod="GMM",data=x,theta0=theta0,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
PrintTime=TRUE,
pm=pm,t_free=t_seq,level=0.92)
## equally
IterationControl <- list(NbIter=8,PrintIter=FALSE,RelativeErrMax=1e-2)
t_scheme="equally"
algo="ITGMM"
regularization="Tikhonov"
WeightingMatrix="DataVar"
objequally <- Estim(EstimMethod="GMM",data=x,theta0=theta0,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
pm=pm,
PrintTime=TRUE,nb_t=42,Constrained=TRUE,
tol=1e-3,maxIter=100,lowerBand=0.01,
upperBand=10,min_t=0.1,max_t=3)
## NonOptAr
t_scheme="NonOptAr"
algo="CueGMM"
regularization="LF"
WeightingMatrix="OptAsym"
objNonOptAr <- Estim(EstimMethod="GMM",data=x,theta0=theta0,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
pm=pm,
PrintTime=TRUE,nb_t=42,Constrained=FALSE,
tol=1e-3,maxIter=100,lowerBand=0.01,
upperBand=10,min_t=0.1)
list(NonOptAr=objNonOptAr,equally=objequally,free=objfree)
}
example.GMM.opt <- function(index=1){
theta <- c(1.13,0.23,1,0)
theta0 <- NULL
pm <- 0
set.seed(345);x <- rstable(500,theta[1],theta[2],theta[3],theta[4],pm)
alphaReg=0.05
IterationControl <- list(NbIter=8,PrintIter=FALSE,RelativeErrMax=1e-2)
if(index==1){##takes 2s
## uniformOpt
t_scheme="uniformOpt"
algo="CueGMM"
regularization="cut-off"
WeightingMatrix="Id"
obj <- Estim(EstimMethod="GMM",data=x,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
pm=pm,
PrintTime=TRUE,nb_t=42,Constrained=TRUE,
tol=1e-3,maxIter=100,lowerBand=0.01,
upperBand=10)
}
else if (index==2){ ## takes 4s
## ArithOpt
t_scheme="ArithOpt"
algo="ITGMM"
regularization="LF"
WeightingMatrix="DataVar"
nb <- 42
obj <- Estim(EstimMethod="GMM",data=x,theta0=theta0,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
pm=pm,
PrintTime=TRUE,nb_t=42,Constrained=TRUE,
tol=1e-3,maxIter=100,lowerBand=0.01,
upperBand=10)
}
else if (index==3){ #takes 22s
## VarOpt
t_scheme="VarOpt"
algo="2SGMM"
regularization="Tikhonov"
WeightingMatrix="OptAsym"
nb <- 42
obj <- Estim(EstimMethod="GMM",data=x,theta0=theta0,
ComputeCov=TRUE,HandleError=FALSE,
algo=algo,alphaReg=alphaReg,
regularization=regularization,
WeightingMatrix=WeightingMatrix,
t_scheme=t_scheme,
IterationControl=IterationControl,
pm=pm,
PrintTime=TRUE,nb_t=nb,
tol=1e-3,maxIter=100,lowerBand=0.01,
upperBand=10)
}
obj
}
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