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I get the following error for a hierarchcial model with only two levels (i.e. top and bottom level) if I try to apply the forecast function to an hts object:
Fehler in utmat %*% fcasts : non-conformable arguments
Zusätzlich: Warnmeldung:
In cbind.Matrix(x, y, deparse.level = 0L) :
number of rows of result is not a multiple of vector length
I'm relatively sure that this code still worked about a year ago. The error does also not occur for a hierarchie with 3 or more levels.
library(hts)
#> Loading required package: forecast#> Registered S3 method overwritten by 'quantmod':#> method from#> as.zoo.data.frame zoo
set.seed(123)
my_ts<- replicate(4, arima.sim(model=list(c(ma=0.8)), n=12))
my_hts<- hts(my_ts)
#> Since argument characters are not specified, the default labelling system is used.
forecast.gts(my_hts, h=4)
#> Hierarchical Time Series #> 2 Levels #> Number of nodes at each level: 1 4 #> Total number of series: 5 #> Number of observations in each historical series: 12 #> Number of forecasts per series: 4 #> Top level series of forecasts: #> Time Series:#> Start = 13 #> End = 16 #> Frequency = 1 #> [1] 0.08870912 0.08870912 0.08870912 0.08870912
I get the following error for a hierarchcial model with only two levels (i.e. top and bottom level) if I try to apply the forecast function to an hts object:
Fehler in utmat %*% fcasts : non-conformable arguments
Zusätzlich: Warnmeldung:
In cbind.Matrix(x, y, deparse.level = 0L) :
number of rows of result is not a multiple of vector length
I'm relatively sure that this code still worked about a year ago. The error does also not occur for a hierarchie with 3 or more levels.
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