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-rw-r--r--R/estpoly.R8
1 files changed, 4 insertions, 4 deletions
diff --git a/R/estpoly.R b/R/estpoly.R
index 9e99dae..0407514 100644
--- a/R/estpoly.R
+++ b/R/estpoly.R
@@ -163,7 +163,7 @@ residplot <- function(model,newdata=NULL){
#'
#' @examples
#' data(arxsim)
-#' model <- arx(data,c(2,1,1))
+#' model <- arx(arxsim,c(2,1,1))
#' model
#' plot(model) # plot the predicted and actual responses
#'
@@ -324,7 +324,7 @@ arx <- function(x,order=c(1,1,1),lambda=0.1,intNoise=FALSE,
#'
#' @examples
#' data(armaxsim)
-#' z <- dataSlice(data,end=1533) # training set
+#' z <- dataSlice(armaxsim,end=1533) # training set
#' mod_armax <- armax(z,c(1,2,1,2))
#' mod_armax
#'
@@ -432,7 +432,7 @@ armax <- function(x,order=c(0,1,1,0),init_sys=NULL,intNoise=FALSE,
#'
#' @examples
#' data(oesim)
-#' z <- dataSlice(data,end=1533) # training set
+#' z <- dataSlice(oesim,end=1533) # training set
#' mod_oe <- oe(z,c(2,1,2))
#' mod_oe
#' plot(mod_oe) # plot the predicted and actual responses
@@ -549,7 +549,7 @@ oe <- function(x,order=c(1,1,0),init_sys=NULL,options=optimOptions()){
#'
#' @examples
#' data(bjsim)
-#' z <- dataSlice(data,end=1500) # training set
+#' z <- dataSlice(bjsim,end=1500) # training set
#' mod_bj <- bj(z,c(2,1,1,1,2))
#' mod_bj
#' residplot(mod_bj) # residual plots