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Add conversion methods between multivariate and univariate forecast types #1119
There are no dedicated conversion methods between multivariate and univariate forecast types. Some conversions already work via default methods, but others need new methods.
What already works
Promoting univariate to multivariate works via the .default constructors:
as_forecast_multivariate_sample(forecast_sample_obj, joint_across = "location") works because the .default method calls as_forecast_generic() which strips/rebuilds the object, then ensure_mv_grouping() adds .mv_group_id.
as_forecast_multivariate_point(forecast_point_obj, joint_across = "location") works the same way.
Existing univariate conversions for reference:
as_forecast_quantile.forecast_sample converts samples to quantiles
as_forecast_point.forecast_quantile extracts the median as a point forecast
Summarise samples to multivariate point predictions (e.g. via mean or median per forecast unit). Should follow the as_forecast_point.forecast_quantile pattern:
Assert input is valid multivariate sample
Aggregate predicted values per forecast unit (configurable summary function, default mean)
Remove sample_id column
Preserve .mv_group_id and grouping structure
Return forecast_multivariate_point object
as_forecast_point.forecast_multivariate_sample
Same as above but also drops the multivariate grouping:
Aggregate predicted values per forecast unit
Remove sample_id and .mv_group_id columns
Return forecast_point object
Could be implemented as: convert to multivariate point first, then drop grouping. Or directly in one step.
as_forecast_point.forecast_multivariate_point
Downgrade by stripping multivariate grouping:
Remove .mv_group_id column
Return forecast_point object
as_forecast_quantile.forecast_multivariate_sample
Analogous to the existing as_forecast_quantile.forecast_sample but drops the multivariate grouping. Could delegate to the existing sample-to-quantile method after stripping .mv_group_id.
Activity
seabbs commentedon Feb 16, 2026
These seem worth having. Happy to allocate to @seabbs-bot
nikosbosse commentedon May 31, 2026
Agree this would be nice