StudentsTLikelihood.h

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2013 Roman Votyakov
 * Copyright (C) 2012 Jacob Walker
 * Copyright (C) 2013 Roman Votyakov
 *
 * Code adapted from the GPML Toolbox:
 * http://www.gaussianprocess.org/gpml/code/matlab/doc/
 */

#ifndef CSTUDENTSTLIKELIHOOD_H_
#define CSTUDENTSTLIKELIHOOD_H_

#include <shogun/lib/config.h>

#ifdef HAVE_EIGEN3

#include <shogun/machine/gp/LikelihoodModel.h>

namespace shogun
{

class CStudentsTLikelihood: public CLikelihoodModel
{
public:
    CStudentsTLikelihood();

    CStudentsTLikelihood(float64_t sigma, float64_t df);

    virtual ~CStudentsTLikelihood();

    virtual const char* get_name() const { return "StudentsTLikelihood"; }

    float64_t get_sigma() { return m_sigma; }

    void set_sigma(float64_t sigma)
    {
        REQUIRE(sigma>0.0, "Scale parameter must be greater than zero\n")
        m_sigma=sigma;
    }

    float64_t get_degrees_freedom() { return m_df; }

    void set_degrees_freedom(float64_t df)
    {
        REQUIRE(df>1.0, "Number of degrees of freedom must be greater than one\n")
        m_df=df;
    }

    static CStudentsTLikelihood* obtain_from_generic(CLikelihoodModel* likelihood);

    virtual SGVector<float64_t> get_predictive_means(SGVector<float64_t> mu,
            SGVector<float64_t> s2, const CLabels* lab=NULL) const;

    virtual SGVector<float64_t> get_predictive_variances(SGVector<float64_t> mu,
            SGVector<float64_t> s2, const CLabels* lab=NULL) const;

    virtual ELikelihoodModelType get_model_type() const { return LT_STUDENTST; }

    virtual SGVector<float64_t> get_log_probability_f(const CLabels* lab,
            SGVector<float64_t> func) const;

    virtual SGVector<float64_t> get_log_probability_derivative_f(
            const CLabels* lab, SGVector<float64_t> func, index_t i) const;

    virtual SGVector<float64_t> get_first_derivative(const CLabels* lab,
            SGVector<float64_t> func, const TParameter* param) const;

    virtual SGVector<float64_t> get_second_derivative(const CLabels* lab,
            SGVector<float64_t> func, const TParameter* param) const;

    virtual SGVector<float64_t> get_third_derivative(const CLabels* lab,
            SGVector<float64_t> func, const TParameter* param) const;

    virtual SGVector<float64_t> get_log_zeroth_moments(SGVector<float64_t> mu,
            SGVector<float64_t> s2, const CLabels* lab) const;

    virtual float64_t get_first_moment(SGVector<float64_t> mu,
            SGVector<float64_t> s2, const CLabels* lab, index_t i) const;

    virtual float64_t get_second_moment(SGVector<float64_t> mu,
            SGVector<float64_t> s2, const CLabels* lab, index_t i) const;

    virtual bool supports_regression() const { return true; }

private:
    void init();

    float64_t m_sigma;

    float64_t m_df;
};
}
#endif /* HAVE_EIGEN3 */
#endif /* CSTUDENTSTLIKELIHOOD_H_ */