predict()
projects bird distributions into the future or past. Given an
initial distribution and time period specified via ...
, predict()
generates probability distributions for each timestep.
Arguments
- object
A BirdFlow model object.
- distr
A starting distribution.
- ...
Arguments passed on to
lookup_timestep_sequence
season
a season name, season alias, or "all". See
lookup_season_timesteps()
for options.start
The starting point in time specified as a timestep, character date, or date object.
end
The ending point in time as a date or timestep.
direction
Either "forward" or "backward" defaults to
"forward"
if not processing dates. If using date inputdirection
is optional and is only used to verify the direction implicit in the dates.season_buffer
Only used with
season
input.season_buffer
is passed tolookup_season_timesteps()
and defaults to 1; it is the number of timesteps to extend the season by at each end.n_steps
Alternative to
end
The end will ben_steps
away fromstart
indirection
; and the resulting sequence will haven_step
transitions andn_steps + 1
timesteps.
Value
If multiple starting distributions are input in a matrix the result will be an array with dimensions: location, distribution, and time. With one input distribution the result will be a matrix with dimensions: location and time.
See also
lookup_timestep_sequence()
processes the time inputs (start
,end
,direction
, andseason_buffer
)route()
androute_migration()
are similar topredict()
but generate routes instead of distributions.