LTPDA Toolbox™ | contents | ![]() ![]() |
FISHER.M Calculation of the fisher Information Matrix/Covariance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% INPUTS: - The MFH object - The set of parameters x. - The inverse cross-spectrum matrix S (in structure array, see function MCMC.ao2structArrays). - DStep. The set of derivative steps. (double vactor). OUTPUTS: - Covariance matrix of the parameters.
Method Details | |
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Access | public |
Defining Class | mfh |
Sealed | 0 |
Static | 0 |
Sets for this method … |
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Default |
Default |
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no description | |||
Key | Default Value | Options | Description |
FITPARAMS | '' | none | (Optional) The Parameter names of the model. |
PARAMSVALUES | '' | none | The numerical values of the parameters. |
PINV | 1 |
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Use the Penrose-Moore pseudoinverse |
TOL | [] | none | Tolerance for the Penrose-Moore pseudoinverse |
DIFFSTEP | [] | none | Numerical differentiation step for ssm models |
LOG PARAMETERS | [] | none | An array with upper and lower values for the parameters ranges. To be used to compute the optimal differentiation step for ssm models. |
NOISE | [] | none | The inverse cross-spectrum matrix of the noise. Must be either an AO or a MATRIX object |
Some information of the method mfh/fisher are listed below: | |
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Class name | mfh |
Method name | fisher |
Category | Signal Processing |
Package name | ltpda |
VCS Version | 3542afe99dea25c636b7ac3b82a9f6f8be9d447d |
Min input args | 1 |
Max input args | -1 |
Min output args | 1 |
Max output args | -1 |
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Method: mfh/ne | Method: mfh/fminsearch | ![]() |
©LTP Team