M3Forecast | R Documentation |
The forecasts from all the original participating methods in the M3 forecasting competition.
M3Forecast
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.
Christoph Bergmeir and Rob Hyndman
http://forecasters.org/resources/time-series-data/m3-competition/.
Makridakis and Hibon (2000) The M3-competition: results, conclusions and implications. International Journal of Forecasting, 16, 451-476.
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)
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