Estim {StableEstim} | R Documentation |
Estimate parameters of stable laws
Description
Estimates the four parameters of stable distributions using one of the methods implemented in StableEstim. This is the main user-level function but the individul methods are available also as separate functions.
Usage
Estim(EstimMethod = c("ML", "GMM", "Cgmm","Kout"), data, theta0 = NULL,
ComputeCov = FALSE, HandleError = TRUE, ...)
Arguments
EstimMethod |
Estimation method to be used, one of |
data |
Data used to perform the estimation, a numeric vector. |
theta0 |
Initial values for the 4 parameters. If |
ComputeCov |
Logical flag: if |
HandleError |
Logical flag: if |
... |
Other arguments to be passed to the estimation function, such as the asymptotic confidence level, see Details. |
Details
Estim
is the main estimation function in package
StableEstim.
This function should be used in priority for estimation purpose as it
provides more information about the estimator. However, user needs to
pass the appropriate parameters to the selected method in
...
. See the documentation of the selected method.
Asymptotic Confidence Intervals:
The normal asymptotic confidence intervals (CI) are computed.
The user can set the level of confidence by inputing the
level
argument (in the "\dots"
); default
level=0.95
. The theoretical justification for asymptotic normal
CI can be found in the references for the individual methods. Note the
CI's are not computed for the Koutrouvelis regression method.
Value
an object of class Estim
, see Estim-class
for
more details
See Also
CgmmParametersEstim
,
GMMParametersEstim
,
MLParametersEstim
,
KoutParametersEstim
for the individual estimation
methods;
IGParametersEstim
for fast computation of initial
values.
Examples
## general inputs
theta <- c(1.45, 0.55, 1, 0)
pm <- 0
set.seed(2345)
x <- rstable(200, theta[1], theta[2], theta[3], theta[4], pm)
objKout <- Estim(EstimMethod = "Kout", data = x, pm = pm,
ComputeCov = FALSE, HandleError = FALSE,
spacing = "Kout")