student_t_process_jef.hpp

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/*
-------------------------------------------------------------------------
   This file is part of BayesOpt, an efficient C++ library for 
   Bayesian optimization.

   Copyright (C) 2011-2015 Ruben Martinez-Cantin <rmcantin@unizar.es>
 
   BayesOpt is free software: you can redistribute it and/or modify it 
   under the terms of the GNU Affero General Public License as published by
   the Free Software Foundation, either version 3 of the License, or
   (at your option) any later version.

   BayesOpt is distributed in the hope that it will be useful, but 
   WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU Affero General Public License for more details.

   You should have received a copy of the GNU Affero General Public License
   along with BayesOpt.  If not, see <http://www.gnu.org/licenses/>.
------------------------------------------------------------------------
*/


#ifndef __STUDENT_T_PROCESS_JEF_HPP__
#define __STUDENT_T_PROCESS_JEF_HPP__

#include "student_t_distribution.hpp"
#include "gaussian_process_hierarchical.hpp"


namespace bayesopt
{
  
  class StudentTProcessJeffreys: public HierarchicalGaussianProcess
  {
  public:
    StudentTProcessJeffreys(size_t dim, Parameters params, const Dataset& data, 
             MeanModel& mean, randEngine& eng);
    virtual ~StudentTProcessJeffreys();

    ProbabilityDistribution* prediction(const vectord &query);

  private:

    double negativeLogLikelihood();

    void precomputePrediction();

  private:
    vectord mWML;           
    vectord mKn;
    vectord mAlphaF;
    matrixd mKF, mL2;

    StudentTDistribution* d_;      
  };

} //namespace bayesopt

#endif