Find likelihood from state space with Kalman filter

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Rob
Rob am 24 Nov. 2022
Kommentiert: Rob am 29 Nov. 2022
Hi everyone,
I'm struggeling to find the correct solution approach for my problem, despite screening the forum for an answer. I have a state space system with the respective A, B, C and D matrices and successfully used
state_space = ssm(A,B,C,D) ;
The respictive sizes of the matrices are:
>> size(A)
ans =
27 27
>> size(B)
ans =
27 9
>> size(C)
ans =
9 27
>> size(D)
ans =
9 9
There is also an observation matrix y which is a 155 x 9 matrix. Can anyone point me into the right direction how I can find the likelihood function of this system, using the Kalman filter. Or would I have to code this myself, as there's no command available? Many thanks for your help!
Rob

Akzeptierte Antwort

Sam Chak
Sam Chak am 25 Nov. 2022
Hi @Rob
Perhaps you are looking for the likelihood() function.
help likelihood
--- help for trackingEKF/likelihood --- LIKELIHOOD Calculate the likelihood of a measurement l = likelihood(EKF, Z) calculates the likelihood of a measurement, Z, given the object, EKF. l = likelihood(EKF, Z, measurementParams) allows you to define additional parameters that will be used by the EKF.MeasurementFcn. It should be specified as a cell array, e.g., {1, [2;3]}. If unspecified, it will be assumed to be an empty cell array. Documentation for trackingEKF/likelihood doc trackingEKF/likelihood Other uses of likelihood AlphaBetaFilter/likelihood ggiwphd/likelihood matlabshared.tracking.internal.AbstractTrackingFilter/likelihood
  2 Kommentare
Rob
Rob am 25 Nov. 2022
Thanks @Sam Chak let me give this a try and report back!
Rob
Rob am 29 Nov. 2022
Hi @Sam Chak, your answer might go into the right direction but I am still in the process of working things out. Thanks for your help!

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