Package stallone.hmm

Examples of stallone.hmm.EM

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        boolean eventBased = true;

        // save memory?
        boolean saveMemory = false;

        IExpectationMaximization em = new EM(_obs, eventBased, initialParameters.getNStates(), initialParameters.isReversible(), outputModel, outputEstimator, saveMemory);
        em.setInitialParameters(initialParameters);

        return em;
    }
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        // count states:
        int nstates = IntSequence.util.max(initialPaths)+1;

        // construct em:
        IExpectationMaximization em = new EM(_obs, eventBased, nstates, reversible, outputModel, outputEstimator, saveMemory);
        // default parameters:
        IHMMParameters par0 = parameters(nstates, reversible, true, outputModel);
        em.setInitialParameters(par0);

        em.setInitialPaths(initialPaths);

        return em;
    }
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        boolean saveMemory = false;

        // output model and parametrizer
        DiscreteDistribution dd = new DiscreteDistribution(initialParameters.getOutputParameters(0));
        dd.setPrior(prior);
        EM em = new EM(_obs, eventBased, initialParameters.getNStates(), initialParameters.isReversible(), dd, dd, saveMemory);
        em.setInitialParameters(initialParameters);

        return em;
    }
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        // save memory?
        boolean saveMemory = false;

        // output model and parametrizer
        DiscreteDistribution dd = new DiscreteDistribution(initialParameters.getOutputParameters(0));
        EM em = new EM(_obs, eventBased, initialParameters.getNStates(), initialParameters.isReversible(), dd, dd, saveMemory);
        em.setInitialParameters(initialParameters);

        return em;
    }
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        // save memory?
        boolean saveMemory = false;
        // output model and parametrizer
        GaussianUnivariate gauss = new GaussianUnivariate(0,1);
        EM em = new EM(_obs, eventBased, initialParameters.getNStates(), initialParameters.isReversible(), gauss, gauss, saveMemory);
        em.setInitialParameters(initialParameters);

        return em;
    }
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        GaussianUnivariate gauss = new GaussianUnivariate(0,1);

        // count states:
        int nstates = IntSequence.util.max(initialPaths)+1;

        EM em = new EM(_obs, eventBased, nstates, reversible, gauss, gauss, saveMemory);
        em.setInitialPaths(initialPaths);

        return em;
    }
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Related Classes of stallone.hmm.EM

  • stallone.api.doubles.IDoubleArray
  • stallone.api.hmm.HMMFactory
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