Corrected some errors and updated documentation

4 files changed, 7 insertions, 6 deletions

diff --git a/NAMESPACE b/NAMESPACE
index 0f762cb..fa778d3 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -60,3 +60,4 @@ export(spa)
 export(step)
 export(tf)
 import(tframe)
+importFrom(zoo,na.approx)
diff --git a/R/idframe.R b/R/idframe.R
index aed020d..265bca7 100644
--- a/R/idframe.R
+++ b/R/idframe.R
@@ -32,7 +32,7 @@ idframe <- function(output=NULL,input=NULL,Ts = 1,start=0,end=NULL,
     start <- end - Ts*(n-1)
   } 
   
-  l3 <- lapply(l,ts,start=start,deltat=1/Ts)
+  l3 <- lapply(l,ts,start=start,deltat=Ts)
   
   # Object Constructor
   dat <- list(output=l3[[1]],input=l3[[1]],unit=unit)
@@ -73,7 +73,7 @@ summary.idframe <- function(x){
   out_sum <- summary(outputData(x))
   in_sum <- summary(inputData(x))
   
-  out <- list(out_sum=out_sum,in_sum=in_sum,Ts=deltat(x)),
+  out <- list(out_sum=out_sum,in_sum=in_sum,Ts=deltat(x),
               unit=x$unit,nsample = dim(outputData(x))[1])
   
   class(out) <- "summary.idframe"
diff --git a/man/dataSlice.Rd b/man/dataSlice.Rd
index cd3af74..5ff6f00 100644
--- a/man/dataSlice.Rd
+++ b/man/dataSlice.Rd
@@ -9,9 +9,9 @@ dataSlice(data, start = NULL, end = NULL, freq = NULL)
 \arguments{
 \item{data}{an object of class \code{idframe}}
 
-\item{start}{the start time of the period of interest}
+\item{start}{the start index}
 
-\item{end}{the end time of the period of interes}
+\item{end}{the end index}
 
 \item{freq}{fraction of the original frequency at which the series
 to be sampled.}
diff --git a/man/predict.detrend.Rd b/man/predict.detrend.Rd
index f5fbf40..87b751f 100644
--- a/man/predict.detrend.Rd
+++ b/man/predict.detrend.Rd
@@ -20,8 +20,8 @@ Returns detrended \code{idframe} object based on linear trend fit
 }
 \examples{
 data(cstr)
-train <- dataSlice(cstr,end=5000) # subset the first 5000 indices
-test <- dataSlice(cstr,start=6001) # subset from index 6001 till the end
+train <- dataSlice(cstr,end=5000)
+test <- dataSlice(cstr,start=6001)
 fit <- detrend(train)
 Ztrain <- predict(fit)
 Ztest <- predict(fit,test)