Given a list of simulation sensitivities, this function returns the
fisher information (sum over all experiments). The actual work is
done in the returned function that implicitly depends on the model,
experiments, and parameter mapping
Usage
fisherInformationFunc(
model,
experiments,
parMap = identity,
parMapJac = function(x) {
diag(1, length(x))
}
)
Arguments
- model
list of R functions for the ODE model
- experiments
list of experiments, with inputs
- parMap
mapping between MCMC variables and ODE parameters
- parMapJac
the jacobian of the above map
Value
fisher information calculating funciton
Details
return value: function(par, simulations, sensitivity) ->
fisherInformation (matrix)
where par refers to the model parameters
(possibly transformed), and simulations performed with those
parameters.