Open christophsax opened 5 years ago
library(tempdisagg)
For usual frequencies, things work like this:
lf = ts(1:4, start = 1989, freq = 1) hf = ts(1:16, start = 1989, freq = 4) predict(td(formula = lf~hf, conversion = 'first')) #> Qtr1 Qtr2 Qtr3 Qtr4 #> 1989 1.00 1.25 1.50 1.75 #> 1990 2.00 2.25 2.50 2.75 #> 1991 3.00 3.25 3.50 3.75 #> 1992 4.00 4.25 4.50 4.75
Howeever, for super-annual frequencies, this does not work:
lf = ts(1:4, start = 1989, freq = 1/2) hf = ts(1:8, start = 1989, freq = 1) predict(td(formula = lf~hf, conversion = 'first')) #> High frequency series shorter than low frequency. Discarding low frequency after 1994. #> Error in SubRegressionBased(y_l = y_l, X = X, hf = hf, lf = lf, lf.end = lf.end, : identical(dim(C)[2], dim(X)[1]) is not TRUE
Seems to be related to the following line in td:
td
n.fc <- as.integer(round((X.end - end) * f)) - fr + 1L
Which is calculated as 1 for the example above but should be 0.
This probably needs a few tests for the usual frequencies, as a change to the formula is likely to break stuff.
Some experiments in https://github.com/christophsax/tempdisagg/tree/triennial
For usual frequencies, things work like this:
Howeever, for super-annual frequencies, this does not work:
Seems to be related to the following line in
td
:Which is calculated as 1 for the example above but should be 0.
This probably needs a few tests for the usual frequencies, as a change to the formula is likely to break stuff.