When you first run PEST, it runs in
parameter estimation mode. This selects values for the input parameters
which cause the outputs to most closely follow the measured values,
according to the least-squares rule. The quality of fit is given by PHI
The purpose of predictive analysis is to
determine the range over which a model output can vary while still being
consistent with the measured values supplied. To get maximum and minimum
predictions, PEST allows the PHI value to be larger than the minimum value
found during parameter estimation.
To do a predictive analysis on a Simile
model, check the checkbox in the predictive analysis frame on the Actions
tab, and select a model value for which to make a prediction. This can be
any non-parameter value in the model, not including those in
variable-membership submodels. It can be a value which you are already
using for comparison with measured data
are using data measured up to a certain point in time to calibrate the
model but then want to predict how the same value will behave at later
times on the basis of this calibration, or even use prediction to fill in a
gap in your measured data.
You can also make the following
selections:
Whether to predict maximum or minimum
values
What multiple of the original PHI to allow
for the predictions
At what time(s) the prediction will
apply.
There are some values on the Settings tab
which affect PEST's behaviour during predictive analysis; these are
explained in the PEST manual. Simile supplies default values for these,
based on the results obtained when running PEST in parameter estimation
mode.
If the value being predicted is an array,
or if the frequency and duration you set for prediction times are such that
a prediction will be made at more than one time, then a complete run of
PEST must be done for each prediction, because PEST itself can only predict
one value at a time. Since each PEST run includes multiple model runs,
predicting large numbers of values can take a very long time. The following
steps might speed things up:
Set display interval to 0, so display
tools do not take up time
Select 'use current values as estimates'
on the Inputs tab after the parameter estimation run, so each prediction
run starts with good parameter estimates.
During a prediction run, the progress bar
shows how many of the prediction runs have been completed. Predicted values
will be inserted into the results field, and can be displayed in tabular
form and saved as a .csv file using the View button.
It is worth noting that each prediction is
arrived at independently. So, if using predictive analysis to create 'error
bands' around a graph of model outputs, it might be the case that although
each individual value might vary as far as the predicted limits, it would
be impossible for the graph line to actually follow the minimum or maximum
limits, since multiple predicted values on the limit might be incompatible
with each other. Remember, however clever PEST might appear, it's still
only a computer program.
In: Contents >> Running
models >> PEST