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diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
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-#' @title get Forecast
-#'
-#' @description Predict time-series curves for the selected days indices (lines in data).
-#'
-#' @param data Dataset, object of type \code{Data} output of \code{getData}
-#' @param indices Days indices where to forecast (the day after)
-#' @param forecaster Name of the main forcaster
-#' \itemize{
-#'   \item Persistence : use values of last (similar, next) day
-#'   \item Neighbors : use values from the k closest neighbors' tomorrows
-#'   \item Average : global average of all the (similar) "tomorrow of past"
-#'   \item Zero : just output 0 (benchmarking purpose)
-#' }
-#' @param pjump How to predict the jump at the interface between two days ?
-#' \itemize{
-#'   \item Persistence : use last (similar) day values
-#'   \item Neighbors: re-use the weights optimized in corresponding forecaster
-#'   \item Zero: just output 0 (no adjustment)
-#' }
-#' @param memory Data depth (in days) to be used for prediction
-#' @param horizon Number of time steps to predict
-#' @param ... Additional parameters for the forecasting models
-#'
-#' @return A list with the following items
-#' \itemize{
-#'   \item serie: forecasted serie
-#'   \item params: corresponding list of parameters (weights, neighbors...)
-#'   \item index: corresponding index in data object
-#' }
-#'
-#' @examples
-#' ts_data = system.file("extdata","pm10_mesures_H_loc.csv",package="talweg")
-#' exo_data = system.file("extdata","meteo_extra_noNAs.csv",package="talweg")
-#' data = getData(ts_data, exo_data, input_tz = "Europe/Paris",
-#'   working_tz="Europe/Paris", predict_at=7)
-#' pred = computeForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12)
-#' \dontrun{#Sketch for real-time mode:
-#' data = new("Data", ...)
-#' forecaster = new(..., data=data)
-#' repeat {
-#'   data$append(some_new_data)
-#'   pred = forecaster$predict(data$getSize(), ...)
-#'   #do_something_with_pred
-#' }}
-#' @export
-computeForecast = function(data, indices, forecaster, pjump,
-	memory=Inf, horizon=data$getStdHorizon(), ...)
-{
-	# (basic) Arguments sanity checks
-	horizon = as.integer(horizon)[1]
-	if (horizon<=0 || horizon>length(data$getCenteredSerie(2)))
-		stop("Horizon too short or too long")
-	indices = sapply( seq_along(indices), function(i) dateIndexToInteger(indices[i], data) )
-	if (any(indices<=0 | indices>data$getSize()))
-		stop("Indices out of range")
-	indices = sapply(indices, dateIndexToInteger, data)
-	if (!is.character(forecaster))
-		stop("forecaster (name) should be of class character") #pjump could be NULL
-
-	pred = Forecast$new()
-	forecaster_class_name = getFromNamespace(paste(forecaster,"Forecaster",sep=""), "talweg")
-	forecaster = forecaster_class_name$new(data=data,
-		pjump = getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
-	for (today in indices)
-	{
-		pred$append(
-			new_serie = forecaster$predictSerie(today, memory, horizon, ...),
-			new_params = forecaster$getParameters(),
-			new_index = today
-		)
-	}
-	pred
-}