diff options
| -rw-r--r-- | R/preprocess.R | 12 | ||||
| -rw-r--r-- | man/predict.detrend.Rd | 4 |
2 files changed, 10 insertions, 6 deletions
diff --git a/R/preprocess.R b/R/preprocess.R index cb7a7ee..698e016 100644 --- a/R/preprocess.R +++ b/R/preprocess.R @@ -64,7 +64,7 @@ detrend <- function(x,type=c("constant","linear")[1]){ end=tail(reg,n=1),deltat=deltat(x)) } - est <- list(fitted.values=data_detrend,output_trend = output_trend, + est <- list(fitted.values=Z,output_trend = output_trend, input_trend = input_trend) class(est) <- "detrend" @@ -75,7 +75,7 @@ detrend <- function(x,type=c("constant","linear")[1]){ #' #' Returns detrended \code{idframe} object based on linear trend fit #' -#' @param object an object of class \code{idframe} +#' @param model an object of class \code{detrend} #' @param newdata An optional idframe object in which to look for variables with #' which to predict. If ommited, the original detrended idframe object is used #' @@ -99,15 +99,19 @@ predict.detrend <- function(model,newdata=NULL,...){ # checking if the original data has outputs if(!is.null(model$output_trend)){ - y <- ts(sapply(output_trend,predict,newdata=data.frame(reg=reg)), + y <- ts(sapply(model$output_trend,predict, + newdata=data.frame(reg=reg)), start=reg[1],end=tail(reg,n=1),deltat = deltat(x)) outputData(x) <- outputData(x) - y + outputNames(x) <- outputNames(newdata) } if(!is.null(model$input_trend)){ - y <- ts(sapply(in_trend,predict,newdata=data.frame(reg=reg)), + y <- ts(sapply(model$input_trend,predict, + newdata=data.frame(reg=reg)), start=reg[1],end=tail(reg,n=1),deltat = deltat(x)) inputData(x) <- inputData(x) - y + inputNames(x) <- inputNames(newdata) } } return(x) diff --git a/man/predict.detrend.Rd b/man/predict.detrend.Rd index 87b751f..e969de9 100644 --- a/man/predict.detrend.Rd +++ b/man/predict.detrend.Rd @@ -4,10 +4,10 @@ \alias{predict.detrend} \title{Detrend data based on linear trend fits} \usage{ -\method{predict}{detrend}(object, newdata = NULL, ...) +\method{predict}{detrend}(model, newdata = NULL, ...) } \arguments{ -\item{object}{an object of class \code{idframe}} +\item{model}{an object of class \code{detrend}} \item{newdata}{An optional idframe object in which to look for variables with which to predict. If ommited, the original detrended idframe object is used} |