ecoXCorr() function with
multiple time series (i.e. when duplicated dates are found in
meteo_data)aggregate_lagged_intervals() now supports multiple
independent time series via a new id_col argument. When
specified, lagged aggregations are performed separately within each
group, preventing unintended mixing of values across distinct time
series (e.g. sites, stations, individuals).fit_models_by_lag() when
computing R² using performance::r2(). Warnings are now
handled more gracefully, and R² is re-evaluated when possible instead of
returning NA.Fixed aggregation interval: The function
aggregate_lagged_intervals() has been corrected to properly include the
last day of each interval in the aggregation. Previously, intervals were
defined as start <= date < end, which systematically excluded the
final day. This has now been changed to start <= date <= end,
ensuring that all dates within the intended interval are considered when
computing summary statistics. This fix guarantees that the aggregated
results accurately reflect the intervals specified by the user.
In addition, default for parameter shift has been
set to 1, i.e. intervals ends the day preceding
ref_date (this latter being excluded).
Fixed an error occurring in fit_models_by_lag()
during result aggregation:
Error in match.names(clabs, names(xi)) : names do not match previous names
This error occurred when performance::r2() failed (error or
warning) for some models, leading to inconsistent column structures
across elements of the results list. The function now ensures consistent
output structure across all lag windows by:
standardizing R² extraction,
returning properly formatted values even when warnings occur,
preventing failures in
do.call(rbind, results).
glmmTMB).