an expression for the drift coefficient; see details.
sigma
an expression for the diffusion coefficient; see details.
a1, a2
weights or instruments.
c.mean
expressions for the conditional mean.
c.var
expressions for the conditional variance.
guess
initial value of the parameters; see details.
lower
lower bounds for the parameters; see details.
upper
upper bounds for the parameters; see details.
Details
The function linear.mart.ef minimizes a linear martingale
estimating function that is a particular case of the polynomial
martingale estimating functions.
Value
x
a vector of estimates
Author(s)
Stefano Maria Iacus
References
Bibby, B., Soerensen, M. (1995) Martingale estimating functions for discretely
observed diffusion processes, Bernoulli, 1, 17-39.
Examples
set.seed(123)
d <- expression(-1 * x)
s <- expression(1)
x0 <- rnorm(1,sd=sqrt(1/2))
sde.sim(X0=x0,drift=d, sigma=s,N=1000,delta=0.1) -> X
d <- expression(-theta * x)
linear.mart.ef(X, d, s, a1=expression(-x), lower=0, upper=Inf,
c.mean=expression(x*exp(-theta*0.1)),
c.var=expression((1-exp(-2*theta*0.1))/(2*theta)))