MixedTS (version 1.0.4)

mle.MixedTS: Maximum Likelihood Estimation for MixedTS distribution

Description

Estimate MixedTS parameters using the Maximum Likelihood Estimation procedure.

Usage

mle.MixedTS(object, start = list(), Data = NULL, 
          method = "L-BFGS-B", fixed.param = NULL, 
          lower.param = NULL, upper.param = NULL, 
          setSup = NULL, setInf = NULL, N = 2^10)

Arguments

object

an object of class param.MixedTS that contains informations about the model.

start

a list of parameter for the mle.

Data

a numeric object containing the dataset.

method

methods for optimization routine. See optim for more details.

fixed.param

a list of the model parameter that must be fix during optimization routine. Choosing alpha=2 the function returns the estimate parameters for the Normal Variance Mean Mixture distribution.

lower.param

a list containing the lower bound for the parameters.

upper.param

a list containing the upper bound for the parameters.

setSup

Internal parameter. see documentation for dMixedTS for more details.

setInf

Internal parameter. see documentation for dMixedTS for more details.

N

Internal parameter. see documentation for dMixedTS for more details.

Value

• The function returns an object of class MixedTS.qmle.

Examples

# First Example:
# We define the Mixed Tempered Stable using the function setMixedTS.param


ParamEx1<-setMixedTS.param(mu0=0, mu=0, sigma=0.4, a=1.5,
                           alpha=0.8, lambda_p=4, lambda_m=1, Mixing="Gamma")

# We generate a sample using the rMixedTS method
set.seed(100)
Rand1 <- rMixedTS(x=5000,object=ParamEx1, setSup=10,setInf=-10,N=2^9)

# Estimate procedure
est1<-mle.MixedTS(object=Rand1 , setSup=10,setInf=-10,N=2^9)
# Show results

summary(est1)