/*
  Copyright (C) 2006 Steven L. Scott

  This library is free software; you can redistribute it and/or
  modify it under the terms of the GNU Lesser General Public
  License as published by the Free Software Foundation; either
  version 2.1 of the License, or (at your option) any later version.

  This library 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
  Lesser General Public License for more details.

  You should have received a copy of the GNU Lesser General Public
  License along with this library; if not, write to the Free Software
  Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA
*/
#ifndef BOOM_MVN_GIVEN_SIGMA_HPP
#define BOOM_MVN_GIVEN_SIGMA_HPP

#include <Models/MvnBase.hpp>
#include <Models/Policies/SufstatDataPolicy.hpp>
#include <Models/Policies/PriorPolicy.hpp>
#include <Models/Policies/ParamPolicy_2.hpp>

namespace BOOM{

  class MvnGivenSigma
    : public MvnBase,
      public LoglikeModel,
      public ParamPolicy_2<VectorParams, UnivParams>,
      public SufstatDataPolicy<VectorData, MvnSuf>,
      public PriorPolicy
  {
  public:
    //  This model is y | mu, kappa Sigma ~ N(mu, Sigma/kappa)

    // Sigma is viewed as a fixed constant, not a parameter of the
    // model.  This model is intended for use as a prior for
    // regression coefficients, where Siginv is proportional to XTX.

    // This model can also be a conjugate prior for the mean of an
    // MvnModel, where Sigma is a parameter of that model (but not of
    // this class).

    // comment and changes made on 4/4/2008.  This might break earlier
    // code e.g. for hierarchical models with same mean but different
    // Sigma?

    // See also MvnGivenX.  These priors are similar.  Use this one if
    // X is going to remain fixed, and MvnGivenX if X will change.

    MvnGivenSigma(const Vector &mu, double Kappa);
    MvnGivenSigma(const Vector &mu, double Kappa, const SpdMatrix & Siginv);
    MvnGivenSigma(const Vector &mu, double Kappa, Ptr<SpdData> Sigma);
    MvnGivenSigma(Ptr<VectorParams> mu,
		  Ptr<UnivParams> Kappa);
    MvnGivenSigma(Ptr<VectorParams> mu,
		  Ptr<UnivParams> Kappa,
		  Ptr<SpdData> Sigma);

    MvnGivenSigma(const MvnGivenSigma & rhs);
    MvnGivenSigma * clone()const override;

    void set_Sigma(Ptr<SpdData> Sigma);
    void set_Sigma(const SpdMatrix &V, bool ivar=false);

    Ptr<VectorParams> Mu_prm();
    const Ptr<VectorParams> Mu_prm()const;
    Ptr<UnivParams> Kappa_prm();
    const Ptr<UnivParams> Kappa_prm()const;

    uint dim()const override;
    const Vector & mu() const override;
    double kappa()const;

    void set_mu(const Vector &);
    void set_kappa(double k);
    void mle() override;
    // The argument is a vector with the mean vector first, and then
    // the proportionalyity facctor 'kappa' second.
    double loglike(const Vector &mu_kappa)const override;
    double pdf(Ptr<Data>, bool)const;
    double pdf(Ptr<DataType>, bool)const;

    double Logp(const Vector &x, Vector &g, Matrix &h, uint nd)const override;
    Vector sim()const override;

    // overloads required to conform with the MvnBase interface The
    // 'Sigma' here refers to the vaiance, not the Sigma paramter.
    // i.e. Sigma() returns  Sigma/kappa

    const SpdMatrix & Sigma()const override;
    const SpdMatrix & siginv()const override;
    double ldsi()const override;
    //--------------------------------------------------------


  private:
    Ptr<SpdData> Sigma_;
    void check_Sigma()const;

    mutable SpdMatrix S;
//     virtual const SpdMatrix & Sigma()const;
//     virtual const SpdMatrix & siginv()const;
//     virtual double ldsi()const;
  };

}
#endif // BOOM_MVN_GIVEN_SIGMA_HPP
