C:/programs/etirm/src/ItemParamPriorNormal.cpp

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/*! \file ItemParamPriorNormal.cpp
 
  \brief
  Class derived from ItemParamPrior representing a normal prior distribution
  of item parameters for use in Bayes modal estimation.
 
  mParameter[0] = mean of normal distribution
  mParameter[1] = standard deviation of normal distribution.

  Note the second parameter is the standard deviation, NOT the variance.

  Estimation Toolkit for Item Response Models (ETIRM)
  http://www.smallwaters.com/software/cpp/etirm.html

  Author(s): 
  Werner Wothke, maintenance (http://www.smallwaters.com)
  Brad Hanson (http://www.b-a-h.com/)
  See the file LICENSE for information on usage and redistribution.

  Copyright (C) 2008, Werner Wothke
  Copyright (c) 2000-2001, Bradley A. Hanson
 */

#ifdef ETIRM_NO_DIR_PREFIX
#include "ItemParamPriorNormal.h"
#else
#include "etirm/ItemParamPriorNormal.h"
#endif

#include <cmath> // for log
// for compilers which do not put C library functions in std namespace
#ifdef BOOST_NO_STDC_NAMESPACE
namespace std
{ using ::log;}
#endif

namespace etirm
{

  /*!
   \brief
   Constructor taking vector of parameters.
   
   \param[in]  &param Parameter vector of length 2: param[0] = Normal prior mean, 
     param[1] = Normal prior standard deviation.
     
   Note: The second element of param is the standard deviation, NOT the variance.
   */
  ItemParamPriorNormal::ItemParamPriorNormal(RealVector &param) :
    ItemParamPrior(param)
  {
    variance = param(2) * param(2);
  }

  /*!
    \brief
    Constructor taking mean and standard deviation as arguments.
    
    \param[in]  mean  Normal prior mean.
    \param[in]  sd  Normal prior standard deviation.
    
    Note: The second parameter is the standard deviation, NOT the variance.
   */
  ItemParamPriorNormal::ItemParamPriorNormal(Real mean, Real sd) :
    ItemParamPrior(2)
  {
    if (sd <= 0.0)
      throw RuntimeError("Invalid s.d. for normal prior",
          "ItemParamPriorNormal::ItemParamPriorNormal");

    mParameters[0] = mean;
    mParameters[1] = sd;

    variance = sd * sd;
  }

  /*!
    \brief
    Default constructor - assigns uniform distribution */
  ItemParamPriorNormal::ItemParamPriorNormal() :
    ItemParamPrior(2)
  {
    mParameters[0] = 0.0;
    mParameters[1] = 1.0;

    variance = 1.0;
  }

  /*!
    \brief
    Returns log-density of p.
    
    \param[in] p  Argument of log density function (an item parameter value).
    
    Note: Returns only the part of the log of the density that depends on the parameter.
   */
  Real ItemParamPriorNormal::LogDensity(Real p)
  {
    Real value = p - mParameters[0];
    value *= value;
    value /= -2.0 * variance;

    return value;
  }

  /*!
    \brief
    Returns first derivative of log density.

    \param[in] p  Argument of log density function (an item parameter value).
  
    Note: Returns only the part of the log of the density that depends on the parameter.
   */
  Real ItemParamPriorNormal::DerivLogDensity1(Real p)
  {
    return -(p - mParameters[0])/variance;
  }

  /*!
    \brief
    Returns second derivative of log density.

    \param[in] p  Argument of log density function (an item parameter value).

    Note: Returns 0nly the part of the log of the density that depends on the parameter.
   */
  Real ItemParamPriorNormal::DerivLogDensity2(Real /* p*/)
  {
    return -1.0/variance;
  }

} // namespace etirm

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