[F,FF,Delta,Freq] = fisher(M,NPer,PList,...)
M
[ model ] - Solved model object.
NPer
[ numeric ] - Length of the hypothetical range for which the Fisher information will be computed.
PList
[ cellstr ] - List of parameters with respect to which the likelihood function will be differentiated.
F
[ numeric ] - Approximation of the Fisher information matrix.
FF
[ numeric ] - Contributions of individual frequencies to the total Fisher information matrix.
Delta
[ numeric ] - Kronecker delta by which the contributions in Fi
need to be multiplied to sum up to F
.
Freq
[ numeric ] - Vector of frequencies at which the Fisher information matrix is evaluated.
'chkSstate='
[ true
| false
| cell ] - Check steady state in each iteration; works only in non-linear models.
'deviation='
[ true
| false
] - Exclude the steady state effect at zero frequency.
'exclude='
[ char | cellstr | empty ] - List of measurement variables that will be excluded from the likelihood function.
'percent='
[ true
| false
] - Report the overall Fisher matrix F
as Hessian w.r.t. the log of variables; the interpretation for this is that the Fisher matrix describes the changes in the log-likelihood function in reponse to percent, not absolute, changes in parameters.
'progress='
[ true
| false
] - Display progress bar in the command window.
'refresh='
[ true
| false
] - Refresh dynamic links in each differentiation step.
'solve='
[ true
| false
| cellstr ] - Re-compute solution in each differentiation step; you can specify a cell array with options for the solve
function.
'sstate='
[ true
| false
| cell ] - Re-compute steady state in each differentiation step; if the model is non-linear, you can pass in a cell array with opt used in the sstate
function.