R/J_Neighbors.R

   1 #' Obtain jump forecast by the Neighbors method
   2 #'
   3 #' @inheritParams getForecast
   4 #' @inheritParams getZeroJumpPredict
   5 getNeighborsJumpPredict = function(data, today, memory, horizon, params, ...)
   6 {
   7     first_day = max(1, today-memory)
   8     filter = params$indices >= first_day
   9     indices = params$indices[filter]
  10     weights = params$weights[filter]
  11     if (any(is.na(weights) | is.na(indices)))
  12         return (NA)
  13
  14     gaps = sapply(indices, function(i) {
  15         data$getSerie(i+1)[1] - tail(data$getSerie(i), 1)
  16     })
  17     scal_product = weights * gaps
  18     norm_fact = sum( weights[!is.na(scal_product)] )
  19     sum(scal_product, na.rm=TRUE) / norm_fact
  20 }