nlr (version 0.1-3)

nl.robcorrts: Robust two stage estimate

Description

Robust Two stage estimate for nonlinear regreession model with autocorrelated error. dfr.robcorrts is derivative free version.

Usage

nl.robcorrts(formula, data, start = getInitial(formula, data), 
control = nlr.control(tolerance = 0.001, minlanda = 1/2^10, 
maxiter = 25 * length(start)), correlation =  list(StructName = "NAN",
manualcorr = NULL), robfunc, ...)

Arguments

formula

nl.form object of the nonlinear function model. See nl.form object.

data

list of data with the response and predictor as name of variable.

start

list of starting value parameter, name of parameters must be represented as names of variable in the list.

control

nlr.control object, include tolerance, maxiter,... see nlr.control.

correlation

correlation structure, at the moment parameter of AR(p) process.

robfunc

nl.form object of robust function.

…

any other argument pass to formula or robfunc.

Value

t2st <- nlmest.NLM(formula, data=data, start=st,robfunc=robfunc,vm=vmat,rm=rmat,control=control,...) result <- list(fited=t2st,tm=tm)

fited

nl.fitt.rgn object generated by nlmest.NLM function.

tm

fitted time series model for residuals.

Details

In first stage nonlinear regression parameter estimate by robust MM method, and in second stage autocorrelation structure estimate and finally the generalized MM-estimates the function model parameters.

References

Riazoshams, H., Midi, H., Sharipov, O. S.H, (2010). The Performance of Robust Two Stage Estimator in Nonlinear Regression with autocorrelated Error, Communications in Statistics - Simulation and Computation, 39: 1251-1268.

See Also

nl.corrts, nlmest.NLM, nl.robcorrts, nlsqr.gn, nl.fitt.gn, nlr.control

Examples

# NOT RUN {
xr = trade.ir[, 1]
yr = trade.ir[, 2]
a1 <-  nl.robcorrts( nlrobj5[[18]],data=list(xr = xr, yr = yr),
correlation=list(StructName="corAR1"),
robfunc = nl.robfuncs[["hampel"]])
a1$parameters 
# }