#' Predict time-series curves ("today" from predict_from to horizon) at the selected days
#' indices ("today" from 1am to predict_from-1). This function just runs a loop over all
#' requested indices, and stores the individual forecasts into a Forecast object.
+#' Note: in training stage ts_hat(day+1) = f(ts(day), exo(day+1)),
+#' and in production ts_hat(day+1) = f(ts(day), exo_hat(day+1))
#'
#' @param data Object of class Data, output of \code{getData()}.
#' @param indices Indices where to forecast (the day after); integers relative to the
#' \itemize{
#' \item Persistence : use last (similar) day
#' \item Neighbors: re-use the weights from F_Neighbors
-#' \item Zero: just output 0 (no adjustment)
+#' \item LastValue: start serie with last observed value
+#' \item Zero: no adjustment => use shape prediction only
#' }
-#' If pjump=NULL, then no adjustment is performed (output of \code{predictShape()} is
-#' used directly).
#' @param predict_from First time step to predict.
#' @param memory Data depth (in days) to be used for prediction.
#' @param horizon Last time step to predict.
#' @return An object of class Forecast
#'
#' @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, limit=200)
-#' pred <- computeForecast(data, 100:130, "Persistence", "Zero",
+#' ts_data <- system.file("extdata","intraday_measures.csv",package="talweg")
+#' exo_data <- system.file("extdata","daily_exogenous.csv",package="talweg")
+#' data <- getData(ts_data, exo_data, date_format="%Y-%m-%d %H:%M:%S", limit=200)
+#' pred <- computeForecast(data, 100:130, "Persistence", "LastValue",
#' predict_from=8, memory=50, horizon=12, ncores=1)
#' \dontrun{
#' #Sketch for real-time mode:
stop("Indices out of range")
if (!is.character(forecaster))
stop("forecaster (name): character")
- if (!is.null(pjump) && !is.character(pjump))
- stop("pjump (function): character or NULL")
+ if (!is.character(pjump))
+ stop("pjump (function): character")
pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
forecaster_class_name = getFromNamespace(
paste(forecaster,"Forecaster",sep=""), "talweg")
- if (!is.null(pjump))
- pjump <- getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")
+ pjump <- getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")
forecaster = forecaster_class_name$new(pjump)
computeOneForecast <- function(i)