Description Usage Arguments Value Author(s) References See Also Examples

Using the method of Hyndman et al. (2011), this function optimally combines
the forecasts at all levels of a hierarchical time series. The
`forecast.gts`

calls this function when the `comb`

method
is selected.

1 2 |

`fcasts` |
Matrix of forecasts for all levels of the hierarchical time series. Each row represents one forecast horizon and each column represents one time series from the hierarchy. |

`nodes` |
If the object class is |

`groups` |
If the object class is |

`weights` |
A numeric vector. The default is |

`algorithms` |
An algorithm to be used for computing reconciled
forecasts. See |

`keep` |
Return a |

Return the reconciled `gts`

object or forecasts at the bottom
level.

Alan Lee, Rob J Hyndman and Earo Wang

R. J. Hyndman, R. A. Ahmed, G. Athanasopoulos and H.L. Shang
(2011) Optimal combination forecasts for hierarchical time series.
*Computational Statistics and Data Analysis*, **55**(9), 2579–2589.
http://robjhyndman.com/papers/hierarchical/

Hyndman, R. J., Lee, A., & Wang, E. (2014). Fast computation of reconciled
forecasts for hierarchical and grouped time series. *Working paper
17/14, Department of Econometrics & Business Statistics, Monash University.*
http://robjhyndman.com/working-papers/hgts/

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
# hts example
## Not run: h <- 12
ally <- aggts(htseg1)
allf <- matrix(NA, nrow = h, ncol = ncol(ally))
for(i in 1:ncol(ally))
allf[,i] <- forecast(auto.arima(ally[,i]), h = h)$mean
allf <- ts(allf, start = 51)
y.f <- combinef(allf, get_nodes(htseg1), weights = NULL, keep = "gts", algorithms = "lu")
plot(y.f)
## End(Not run)
# gts example
## Not run: abc <- ts(5 + matrix(sort(rnorm(200)), ncol = 4, nrow = 50))
g <- rbind(c(1,1,2,2), c(1,2,1,2))
y <- gts(abc, groups = g)
h <- 12
ally <- aggts(y)
allf <- matrix(NA,nrow = h,ncol = ncol(ally))
for(i in 1:ncol(ally))
allf[,i] <- forecast(auto.arima(ally[,i]),h = h)$mean
allf <- ts(allf, start = 51)
y.f <- combinef(allf, groups = get_groups(y), keep ="gts", algorithms = "lu")
plot(y.f)
## End(Not run)
``` |

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