M3Forecast {Mcomp}

M3-Competition forecasts of original competition participants

Description

The forecasts from all the original participating methods in the M3 forecasting competition.

Usage

M3Forecast

Format

M3Forecast is a list of data.frames. Each list element is the result of one forecasting method. The data.frame then has the following structure: Each row is the forecast of one series. Rows are named accordingly. In total there are 18 columns, i.e., 18 forecasts. If fewer forecasts than 18 exist, the row is filled up with NA values.

Author(s)

Christoph Bergmeir and Rob Hyndman

Source

http://forecasters.org/resources/time-series-data/m3-competition/.

References

Makridakis and Hibon (2000) The M3-competition: results, conclusions and implications. International Journal of Forecasting, 16, 451-476.

Examples

M3Forecast[["NAIVE2"]][1,]

## Not run: 
# calculate errors using the accuracy function
# from the forecast package

errors <- lapply(M3Forecast, function(f) {
      res <- NULL
      for(x in 1:length(M3)) {
        curr_f <- unlist(f[x,])
        if(any(!is.na(curr_f))) {
          curr_res <- accuracy(curr_f, M3[[x]]$xx)
        } else {
          # if no results are available create NA results
          curr_res <- accuracy(M3[[x]]$xx, M3[[x]]$xx)
          curr_res <- rep(NA, length(curr_res))
        }
        res <- rbind(res, curr_res)
      }
      rownames(res) <- NULL
      res
    })

ind_yearly <- which(unlist(lapply(M3, function(x) {x$period == "YEARLY"})))
ind_quarterly <- which(unlist(lapply(M3, function(x) {x$period == "QUARTERLY"})))
ind_monthly <- which(unlist(lapply(M3, function(x) {x$period == "MONTHLY"})))
ind_other <- which(unlist(lapply(M3, function(x) {x$period == "OTHER"})))

yearly_errors <- t(as.data.frame(lapply(errors, function(x) {colMeans(x[ind_yearly,])})))
quarterly_errors <- t(as.data.frame(lapply(errors, function(x) {colMeans(x[ind_quarterly,])})))
monthly_errors <- t(as.data.frame(lapply(errors, function(x) {colMeans(x[ind_monthly,])})))
other_errors <- t(as.data.frame(lapply(errors, function(x) {colMeans(x[ind_other,])})))

yearly_errors
quarterly_errors
monthly_errors
other_errors

## End(Not run)