[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.