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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/iv.R
+\name{iv4}
+\alias{iv4}
+\title{ARX model estimation using four-stage instrumental variable method}
+\usage{
+iv4(z, order = c(0, 1, 0))
+}
+\arguments{
+\item{z}{an idframe object containing the data}
+
+\item{order}{Specification of the orders: the three integer components
+(na,nb,nk) are the order of polynolnomial A, (order of polynomial B + 1)
+and the input-output delay}
+}
+\value{
+An object of class \code{estpoly} containing the following elements:
+ \item{sys}{an \code{idpoly} object containing the
+ fitted ARX coefficients}
+ \item{fitted.values}{the predicted response}
+ \item{residuals}{the residuals}
+ \item{input}{the input data used}
+ \item{call}{the matched call}
+ \item{stats}{A list containing the following fields: \cr
+ \code{vcov} - the covariance matrix of the fitted coefficients \cr
+ \code{sigma} - the standard deviation of the innovations\cr
+ \code{df} - the residual degrees of freedom}
+}
+\description{
+Estimates an ARX model of the specified order from input-output data using
+the instrument variable method. The estimation algorithm is insensitive to
+the color of the noise term.
+}
+\details{
+Estimation is performed in 4 stages. The first stage uses the arx function. The resulting model generates the
+instruments for a second-stage IV estimate. The residuals obtained from this model are modeled using a sufficently
+high-order AR model. At the fourth stage, the input-output data is filtered through this AR model and then subjected
+to the IV function with the same instrument filters as in the second stage.
+}
+\examples{
+mod_dgp <- idpoly(A=c(1,-0.5),B=c(0.6,-.2),C=c(1,0.6),ioDelay = 2,noiseVar = 0.1)
+u <- idinput(400,"prbs")
+y <- sim(mod_dgp,u,T)
+z <- idframe(y,u)
+mod_iv4 <- iv4(z,c(1,2,2))
+
+}
+\references{
+Lennart Ljung (1999), \emph{System Identification: Theory for the User},
+2nd Edition, Prentice Hall, New York. Section 15.3
+}
+\seealso{
+\code{\link{arx}}, \code{\link{iv4}}
+}
+