limiting.gamma: calculate the value of limiting covariance matrices : Gamma

limiting.gammaR Documentation

calculate the value of limiting covariance matrices : Gamma

Description

To confirm assysmptotic normality of theta estimators.

Usage

limiting.gamma(obj,theta,verbose=FALSE)

Arguments

obj

an yuima or yuima.model object.

theta

true theta

verbose

an option for display a verbose process.

Details

Calculate the value of limiting covariance matrices Gamma. The returned values gamma1 and gamma2 are used to confirm assysmptotic normality of theta estimators. this program is limitted to 1-dimention-sde model for now.

Value

gamma1

a theoretical figure for variance of theta1 estimator

gamma2

a theoretical figure for variance of theta2 estimator

Note

we need to fix this routine.

Author(s)

The YUIMA Project Team

Examples


set.seed(123)

## Yuima
diff.matrix <- matrix(c("theta1"), 1, 1)
myModel <- setModel(drift=c("(-1)*theta2*x"), diffusion=diff.matrix, 
time.variable="t", state.variable="x")
n <- 100
mySampling <- setSampling(Terminal=(n)^(1/3), n=n)
myYuima <- setYuima(model=myModel, sampling=mySampling)
myYuima <- simulate(myYuima, xinit=1, true.parameter=list(theta1=0.6, theta2=0.3))

## theorical figure of theta
theta1 <- 3.5
theta2 <- 1.3

theta <- list(theta1, theta2)
lim.gamma <- limiting.gamma(obj=myYuima, theta=theta, verbose=TRUE)

## return theta1 and theta2 with list
lim.gamma$list

## return theta1 and theta2 with vector
lim.gamma$vec


yuima documentation built on Nov. 14, 2022, 3:02 p.m.

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