get.tfr.prediction | R Documentation |
Function get.tfr.prediction
retrieves results of a prediction and creates an object of class bayesTFR.prediction
. Function has.tfr.prediction
checks an existence of such results. Function available.tfr.predictions
lists predictions available in the given simulation directory.
get.tfr.prediction(mcmc = NULL, sim.dir = NULL, mcmc.dir = NULL,
subdir = "predictions")
has.tfr.prediction(mcmc = NULL, sim.dir = NULL, subdir = "predictions")
available.tfr.predictions(mcmc = NULL, sim.dir = NULL, full.names = FALSE)
mcmc |
Object of class |
sim.dir |
Directory where the prediction is stored. It should correspond to the value of the |
mcmc.dir |
Optional argument to be used only in a special case when the mcmc object contained in the prediction object was estimated in different directory than in the one to which it points to (for example due to moving or renaming the original directory). The argument causes that the mcmc is redirected to the given directory. It can be set to |
subdir |
Subdirectory of |
full.names |
Logical. If |
If mcmc
is not NULL
, the search directory is set to mcmc$meta$output.dir
. This approach assumes that the prediction was stored in the same directory as the MCMC simulation, i.e. the output.dir
argument of the tfr.predict
function was set to NULL
. If it is not the case, the argument mcmc.dir
should be used.
Usually, all predictions are stored in the subdirectory “predictions” of the simulation directory. If the subdirectory has a different name, the argument subdir
should be used. This allows to keep multiple predictions in one (MCMC) simulation directory.
The function available.tfr.predictions
can be used to view all available predictions in the simulation directory.
Function has.tfr.prediction
returns a logical indicating if a prediction exists for the given mcmc
.
Function available.tfr.predictions
returns a vector of directory names containing TFR predictions.
Function get.tfr.prediction
returns an
object of class bayesTFR.prediction
.
Hana Sevcikova
bayesTFR.prediction
, tfr.predict
, summary.bayesTFR.prediction
sim.dir <- file.path(find.package("bayesTFR"), "ex-data", "bayesTFR.output")
pred <- get.tfr.prediction(sim.dir=sim.dir)
summary(pred, country="Canada")
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