added option to specify noise variance

2 files changed, 23 insertions, 11 deletions

diff --git a/R/poly.R b/R/poly.R
index 9ab4fab..77525e3 100644
--- a/R/poly.R
+++ b/R/poly.R
@@ -2,13 +2,15 @@
 #' 
 #' Creates a polynomial model with identifiable coefficients
 #' 
-#' @param A Autoregressive coefficients
-#' @param B,F1 Coefficients of the numerator and denominator respectively
+#' @param A autoregressive coefficients
+#' @param B,F1 coefficients of the numerator and denominator respectively
 #' of the deterministic model between the input and output 
-#' @param C,D Coefficients of the numerator and denominator respectively
+#' @param C,D coefficients of the numerator and denominator respectively
 #' of the stochastic model 
 #' @param ioDelay the delay in the input-output channel
 #' @param Ts sampling interval
+#' @param noiseVar variance of the white noise source (Default=\code{1})
+#' @param unit time unit (Default=\code{"seconds"})
 #' 
 #' @details
 #' Discrete-time polynomials are of the form
@@ -19,7 +21,8 @@
 #' 
 #' @examples
 #' # define output-error model
-#' mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1)
+#' mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1,
+#' noiseVar = 0.1)
 #' 
 #' # define box-jenkins model
 #' B <- c(0.6,-0.2)
@@ -29,8 +32,11 @@
 #' mod_bj <- idpoly(1,B,C,D,F1,ioDelay=1)
 #' 
 #' @export
-idpoly <- function(A=1,B=1,C=1,D=1,F1=1,ioDelay=0,Ts=1){
-  out <- list(A= A,B=B,C=C,D=D,F1=F1,ioDelay = ioDelay,Ts=Ts)
+idpoly <- function(A=1,B=1,C=1,D=1,F1=1,ioDelay=0,Ts=1,
+                   noiseVar=1,unit = c("seconds","minutes",
+                                       "hours","days")[1]){
+  out <- list(A= A,B=B,C=C,D=D,F1=F1,ioDelay = ioDelay,Ts=Ts,
+              noiseVar=noiseVar,unit=unit)
   out$type <- typecheck(out)
   class(out) <- "idpoly"
   return(out)
diff --git a/man/idpoly.Rd b/man/idpoly.Rd
index 3f82594..7c33be9 100644
--- a/man/idpoly.Rd
+++ b/man/idpoly.Rd
@@ -4,20 +4,25 @@
 \alias{idpoly}
 \title{Polynomial model with identifiable parameters}
 \usage{
-idpoly(A = 1, B = 1, C = 1, D = 1, F1 = 1, ioDelay = 0, Ts = 1)
+idpoly(A = 1, B = 1, C = 1, D = 1, F1 = 1, ioDelay = 0, Ts = 1,
+  noiseVar = 1, unit = c("seconds", "minutes", "hours", "days")[1])
 }
 \arguments{
-\item{A}{Autoregressive coefficients}
+\item{A}{autoregressive coefficients}
 
-\item{B, F1}{Coefficients of the numerator and denominator respectively
+\item{B, F1}{coefficients of the numerator and denominator respectively
 of the deterministic model between the input and output}
 
-\item{C, D}{Coefficients of the numerator and denominator respectively
+\item{C, D}{coefficients of the numerator and denominator respectively
 of the stochastic model}
 
 \item{ioDelay}{the delay in the input-output channel}
 
 \item{Ts}{sampling interval}
+
+\item{noiseVar}{variance of the white noise source (Default=\code{1})}
+
+\item{unit}{time unit (Default=\code{"seconds"})}
 }
 \description{
 Creates a polynomial model with identifiable coefficients
@@ -31,7 +36,8 @@ Discrete-time polynomials are of the form
 }
 \examples{
 # define output-error model
-mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1)
+mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1,
+noiseVar = 0.1)
 
 # define box-jenkins model
 B <- c(0.6,-0.2)