Updating NAMESPACE and documentation

5 files changed, 77 insertions, 21 deletions

diff --git a/NAMESPACE b/NAMESPACE
index 5ad6d09..6dc24e8 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -45,6 +45,7 @@ export(inputNames)
 export(misdata)
 export(nInputSeries)
 export(nOutputSeries)
+export(oe)
 export(outputData)
 export(outputNames)
 export(read.idframe)
diff --git a/R/estpoly.R b/R/estpoly.R
index 23c59ad..062bccd 100644
--- a/R/estpoly.R
+++ b/R/estpoly.R
@@ -148,8 +148,7 @@ residplot <- function(model,newdata=NULL){
 #' using the \code{\link{detrend}} function. 
 #' 
 #' @return
-#' An object with classes \code{estARX} and \code{estPoly}, containing 
-#' the following elements:
+#' An object of class \code{estPoly} containing the following elements:
 #' 
 #' \tabular{ll}{
 #'    \code{coefficients} \tab an \code{idpoly} object containing the 
@@ -219,7 +218,7 @@ arx <- function(x,order=c(0,1,0)){
 #' @param x an object of class \code{idframe}
 #' @param order: Specification of the orders: the four integer components 
 #' (na,nb,nc,nk) are the order of polynolnomial A, order of polynomial B 
-#' + 1, order of the polynomial,and the input-output delay respectively
+#' + 1, order of the polynomial C,and the input-output delay respectively
 #' 
 #' @details
 #' SISO ARMAX models are of the form 
@@ -235,8 +234,7 @@ arx <- function(x,order=c(0,1,0)){
 #' using the \code{\link{detrend}} function. 
 #' 
 #' @return
-#' An object with classes \code{estARX} and \code{estPoly}, containing 
-#' the following elements:
+#' An object of class \code{estPoly} containing the following elements:
 #' 
 #' \tabular{ll}{
 #'    \code{coefficients} \tab an \code{idpoly} object containing the 
@@ -330,14 +328,14 @@ armax <- function(x,order=c(0,1,1,0)){
 #' 
 #' @param x an object of class \code{idframe}
 #' @param order: Specification of the orders: the four integer components 
-#' (na,nb,nc,nk) are the order of polynolnomial A, order of polynomial B 
-#' + 1, order of the polynomial,and the input-output delay respectively
+#' (nb,nf,nk) are order of polynomial B + 1, order of the polynomial F,
+#' and the input-output delay respectively
 #' 
 #' @details
-#' SISO ARMAX models are of the form 
+#' SISO OE models are of the form 
 #' \deqn{
-#'    y[k] + a_1 y[k-1] + \ldots + a_{na} y[k-na] = b_{nk} u[k-nk] + 
-#'    \ldots + b_{nk+nb} u[k-nk-nb] + c_{1} e[k-1] + \ldots c_{nc} e[k-nc]
+#'    y[k] + f_1 y[k-1] + \ldots + f_{nf} y[k-nf] = b_{nk} u[k-nk] + 
+#'    \ldots + b_{nk+nb} u[k-nk-nb] + f_{1} e[k-1] + \ldots f_{nf} e[k-nf]
 #'    + e[k] 
 #' }
 #' The function estimates the coefficients using non-linear least squares 
@@ -347,8 +345,7 @@ armax <- function(x,order=c(0,1,1,0)){
 #' using the \code{\link{detrend}} function. 
 #' 
 #' @return
-#' An object with classes \code{estARX} and \code{estPoly}, containing 
-#' the following elements:
+#' An object of class \code{estPoly} containing the following elements:
 #' 
 #' \tabular{ll}{
 #'    \code{coefficients} \tab an \code{idpoly} object containing the 
@@ -370,11 +367,11 @@ armax <- function(x,order=c(0,1,1,0)){
 #' 21.6.3
 #' 
 #' @examples
-#' data(armaxsim)
+#' data(oesim)
 #' z <- dataSlice(data,end=1533) # training set
-#' mod_armax <- armax(z,c(1,2,1,2))
-#' summary(mod_armax) # obtain estimates and their covariances
-#' plot(mod_armax) # plot the predicted and actual responses
+#' mod_oe <- oe(z,c(2,1,2))
+#' summary(mod_oe) # obtain estimates and their covariances
+#' plot(mod_oe) # plot the predicted and actual responses
 #' 
 #' @export
 oe <- function(x,order=c(1,0,1)){
diff --git a/man/armax.Rd b/man/armax.Rd
index 1d4bd2f..d4e5cf5 100644
--- a/man/armax.Rd
+++ b/man/armax.Rd
@@ -11,11 +11,10 @@ armax(x, order = c(0, 1, 1, 0))
 
 \item{order:}{Specification of the orders: the four integer components
 (na,nb,nc,nk) are the order of polynolnomial A, order of polynomial B
-+ 1, order of the polynomial,and the input-output delay respectively}
++ 1, order of the polynomial C,and the input-output delay respectively}
 }
 \value{
-An object with classes \code{estARX} and \code{estPoly}, containing
-the following elements:
+An object of class \code{estPoly} containing the following elements:
 
 \tabular{ll}{
    \code{coefficients} \tab an \code{idpoly} object containing the
diff --git a/man/arx.Rd b/man/arx.Rd
index 73d29b6..0ed53f6 100644
--- a/man/arx.Rd
+++ b/man/arx.Rd
@@ -14,8 +14,7 @@ arx(x, order = c(0, 1, 0))
 the input-output delay}
 }
 \value{
-An object with classes \code{estARX} and \code{estPoly}, containing
-the following elements:
+An object of class \code{estPoly} containing the following elements:
 
 \tabular{ll}{
    \code{coefficients} \tab an \code{idpoly} object containing the
diff --git a/man/oe.Rd b/man/oe.Rd
new file mode 100644
index 0000000..23fcab1
--- /dev/null
+++ b/man/oe.Rd
@@ -0,0 +1,60 @@
+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/estpoly.R
+\name{oe}
+\alias{oe}
+\title{Estimate Output-Error Models}
+\usage{
+oe(x, order = c(1, 0, 1))
+}
+\arguments{
+\item{x}{an object of class \code{idframe}}
+
+\item{order:}{Specification of the orders: the four integer components
+(nb,nf,nk) are order of polynomial B + 1, order of the polynomial F,
+and the input-output delay respectively}
+}
+\value{
+An object of class \code{estPoly} containing the following elements:
+
+\tabular{ll}{
+   \code{coefficients} \tab an \code{idpoly} object containing the
+   fitted coefficients \cr
+   \code{vcov} \tab the covariance matrix of the fitted coefficients\cr
+   \code{sigma} \tab the standard deviation of the innovations\cr
+   \code{df} \tab the residual degrees of freedom \cr
+   \code{fitted.values} \tab the predicted response \cr
+   \code{residuals} \tab the residuals  \cr
+   \code{call} \tab the matched call \cr
+   \code{time} \tab the time of the data used \cr
+   \code{input} \tab the input data used
+ }
+}
+\description{
+Fit an output-error model of the specified order given the input-output data
+}
+\details{
+SISO OE models are of the form
+\deqn{
+   y[k] + f_1 y[k-1] + \ldots + f_{nf} y[k-nf] = b_{nk} u[k-nk] +
+   \ldots + b_{nk+nb} u[k-nk-nb] + f_{1} e[k-1] + \ldots f_{nf} e[k-nf]
+   + e[k]
+}
+The function estimates the coefficients using non-linear least squares
+(Levenberg-Marquardt Algorithm)
+\\
+The data is expected to have no offsets or trends. They can be removed
+using the \code{\link{detrend}} function.
+}
+\examples{
+data(oesim)
+z <- dataSlice(data,end=1533) # training set
+mod_oe <- oe(z,c(2,1,2))
+summary(mod_oe) # obtain estimates and their covariances
+plot(mod_oe) # plot the predicted and actual responses
+}
+\references{
+Arun K. Tangirala (2015), \emph{Principles of System Identification:
+Theory and Practice}, CRC Press, Boca Raton. Sections 14.4.1, 17.5.2,
+21.6.3
+}
+