predict.hydromad {hydromad}  R Documentation 
Generate simulated time series from Hydromad model objects
Description
Generate simulated time series from Hydromad model objects.
Usage
## S3 method for class 'hydromad'
predict(object, newdata = NULL,
which = c("both", "sma", "routing"), ...,
all = TRUE, feasible.set = FALSE, glue.quantiles = NULL,
groups = NULL, FUN = sum,
return_state = FALSE, return_components = FALSE)
Arguments
object 
an object of class hydromad .

newdata 
a ts like object containing a new time series
dataset (replacing the original DATA argument given to the
hydromad function).

which 
selects either the SMA or routing model, or both models (the
default). Note that if which = "routing" , then newdata
is treated as the effective rainfall (U).

... 
any unmatched arguments will generate an error.

all 
if TRUE , return the entire time series for which data
exists. Otherwise, the warmup period (specified as an argument to
hydromad or update ) is stripped off.

feasible.set, glue.quantiles 
if feasible.set is TRUE, then many simulations will be
generated, using all parameter sets in the feasible set. This
must have been previously specified using
defineFeasibleSet . If glue.quantiles is NULL
then all the simulated time series are returned. If it is
c(0,1) then the overall bounds (minimum and maximum at each
time step) are returned. Otherwise the specified quantiles are
estimated using GLUEtype weighting.

groups, FUN 
groups is an optional grouping variable, of the same length
as the observed data in object , used to aggregate the observed
and fitted time series. The function FUN is applied to each
group.

return_state 
passed to the SMA simulation function, to return state variables.

return_components 
passed to the routing simulation function, to return flow components.

Value
simulated time series.
Author(s)
Felix Andrews felix@nfrac.org
See Also
hydromad
,
update.hydromad
[Package
hydromad version 0.918
Index]