Method matrix/modelselect


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    modelselect.m - method to compute the Bayes Factor using
                    RJMCMC, LF, LM, SBIC methods
 
             call - Bxy = modelselect(out,pl)
 
           inputs - out: matrix objects with measured outputs
                    pl:  parameter list
 
          outputs - Bxy:
                    -RJMCMC:
                      an array of AOs containing the evolution
                      of the Bayes factors. (comparing each model 
                      with each other)
 
                    -LM, LF, SBIC:
                      An ao containing the Bayes Factor for the 
                      comparison of 2 models
       
 Parameters Description
 
    N. Karnesis 27/09/2011 
   
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Method Details
Access public
Defining Class matrix
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
METHOD 'RJMCMC'
  • 'RJMCMC'
  • 'LF'
  • 'LM'
  • 'SBIC'
Method to use to compare two (or more) models. The choises available are; RJMCMC, Laplace-Metropolis (LM), Laplace-Fisher (LF) and Schwarz-Bayes Information Criterion (SBIC). Default is RJMCMC.Each method needs some compulsory fields to be filled in the plist.
INNAMES '' none Input names. Used for ssm models
OUTNAMES '' none Output names. Used for ssm models
MODELS '' none A cell array input of models.
FITPARAMS [] none A cell array of evaluated parameters for each model.
INPUT '' none A matrix array of input signals.
N 1000 none number of samples of the chain.
COV 0.0001 none Cell array containing the covariances of the gaussian jumping distribution for each model.
NOISE '' none A matrix array of noise spectrum (PSD) used to compute the likelihood.
MODELFREQDEPENDENT 1
  • 1
  • 0
Set to true to use frequency dependent s models, set to false when using constant models
SEARCH 1
  • 1
  • 0
Set to true to use bigger jumps in parameter space during annealing and cool down.
FREQUENCIES [] none Range of frequencies where the analysis is performed. If an array, only first and last are used
FSOUT [] none Desired sampling frequency to resample the input time series
HEAT 1 none The heat index flattening likelihood surface during annealing.
TC '' none An array of two values setting the initial and final value for the cooling down.
X0 [] none The proposed initial values (cell array again).
RANGE [] none ranges
BURNIN 1 none If method is RJMCMC, choose number of samples to be discarded to compute B.
JUMPS [] none An array of four numbers setting the rescaling of the covariance matrix during the search phase.The first value is the one applied by default, the following thhree apply just when the chain sample ismod(10), mod(25) and mod(100) respectively.
PLOT [] none Case: RJMCMC: If set equal to one, the evolution of the Bayes factor and the Loglikelihoodsare plotted every 500 steps. Case: LM: vector for plotting the chains during the mcmc runs.
DEBUG 0
  • 0
  • 1
Set to true to get debug information of the MCMC process.
OUTMODEL '' none Output model. Still under test
THETAMAP [] none Cell array containing the parameter vectors that maximize the likelihoods for two models. Used for LF, LM, SBIC methods.
SAMPLE 1
  • 1
  • 0
Used in the case of 'LM' method to extract covariance matrices. If true, MCMC parameter estimationis applied for both models. If false, the covariance matrices and parameter values in the 'cov' and 'thetaMAP' fields are used to calculate the evidence.
PRIOR '' none Mean, sigma and normalization factor for priors. Still under test
WIN 0
  • 0
  • 1
Windowing the data.
WIN TYPE 'BH92'
  • 'Rectangular'
  • 'Welch'
  • 'Bartlett'
  • 'Hanning'
  • 'Hamming'
  • 'Nuttall3'
  • 'Nuttall4'
  • 'Nuttall3a'
  • 'Nuttall3b'
  • 'Nuttall4a'
  • 'Nuttall4b'
  • 'Nuttall4c'
  • 'BH92'
  • 'SFT3F'
  • 'SFT3M'
  • 'FTNI'
  • 'SFT4F'
  • 'SFT5F'
  • 'SFT4M'
  • 'FTHP'
  • 'HFT70'
  • 'FTSRS'
  • 'SFT5M'
  • 'HFT90D'
  • 'HFT95'
  • 'HFT116D'
  • 'HFT144D'
  • 'HFT169D'
  • 'HFT196D'
  • 'HFT223D'
  • 'HFT248D'
  • 'Kaiser'
  • 'levelledHanning'
Choose the type of the spectral window.
PSLL 150 none Only if 'win' is set to 'true'. If you choose a 'kaiser' window, you can also specify the peak-sidelobe-level.
LEVELORDER 2 none Only if 'win' is set to 'true'. If you choose a 'levelledHanning' window, you can also specify the order of the contraction.
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Some information of the method matrix/modelselect are listed below:
Class name matrix
Method name modelselect
Category Signal Processing
CVS Version $Id: modelSelect.m,v 1.33 2011/07/31 17:38:34 nikos Exp $
Min input args 1
Max input args -1
Min output args 1
Max output args -1




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