Method mfh/loglikelihood
LOGLIKELIHOOD: Compute log-likelihood for MFH objects
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Compute the (unnormalized) log-likelihood for MFH objects.
For the MFH objects, the log-likelihood function must be defined
by the user. For example, for the definition <o - H x i>*S^-1<o - H x i>
the function 'func' must cover the term <o - H x i>. The 'S' matrix
corresponds to the 'noise' plist key.
EXAMPLE: LLH = loglikelihood(func, pl);
For more than one channel model, then input an array of MFH objects.
NOTE: The 'S' matrix must be of the correct size Nout X Nout.
For example, for the 2 input - 2 output case:
LLH = loglikelihood([ch1_mfh ch2_mfh], plist);
OUTPUTS: logL - A collection of objects containing the LLH, SNR,
LLH(frequencies).
NOTE: If callerIsMethod is true, only the numerical values of the
above items are returned.
Example: [LLH SNR LLH(f)] = loglikelihood(m, plist);
Otherwise, if callerIsMethod == false
collection = loglikelihood(myfunc, plist);
Parameters Description
M. Nofrarias, N. Karnesis 2012
Method Details |
|
Access |
public |
Defining Class |
mfh |
Sealed |
0 |
Static |
0 |
Parameter Description
Sets for this method … |
Default |
Default |
no description |
Key |
Default Value |
Options |
Description |
X |
[] |
none |
The parameter values. A 1xNumParams array. |
NOISE |
[] |
none |
The inverse cross-spectrum matrix of the measured noise. |
F |
[] |
none |
Numerical array of frequencies. |
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Some information of the method mfh/loglikelihood are listed below: |
Class name |
mfh |
Method name |
loglikelihood |
Category |
Signal Processing |
Package name |
ltpda |
VCS Version |
8ab8cbbc4bccf7543491a24448f4aae0b1be1c43 |
Min input args |
1 |
Max input args |
-1 |
Min output args |
1 |
Max output args |
-1 |
|
Method: mfh/getJacobian |
|
Method: mfh/paramCovMat |
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©LTP Team