Closed srlanalytics closed 5 years ago
m$idx_update
is now a multiple time series and can be accessed, e.g., by:
window(m$idx_update, start = c(2018, 12), end = c(2018, 12))
Adjusted example in us_gdp.R
.
We should include a section on this in the vignette, this seems important.
Has a section now, 'Forecast Updates', including a nice ggplot
The gain_and_fit branch has been modified so that:
if
store_idx
is specified, the forecast update contribution of each variable to the series specified bystore_idx
. The example us_gdp.R now includes an example of the contribution of each series to nowcast updates for a specified period. Updates to a specific series are stored asidx_update
. Ifscale = T
is specified (the default), forecast updates are unscaled before being returned. However, they remain in logs and/or differenced, so that these updates can be interpreted as percent change to the original variable.in every case, forecast updates to factors are stored in
factor_update
gain and prediction error are no longer returned as updates are a far more concise and useful way to save this information. Advanced users can still access gain and prediction error through
Cppbdfm()
.@christophsax ---
idx_update
andforecast_update
are lists. Right now individual elements can only be accessed by index (i.e.est$idx_update[[460]]
). If input data arets_boxable()
it would be nice to be able to call these results by date (i.e. what was the contribution of each series to the nowcast on 2018-03-31?). Any ideas on the best way to do this?