logisticK.cpp

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#include <admodel.h>
#include <df1b2fun.h>
#include <adrndeff.h> 

/*---------------------------------------------------------3rd variable is a scalar*/
/*---------------------------------------------2nd variable is a scalar*/
dvariable logisticK( const double& t,  const prevariable& K,  const prevariable& r,  const prevariable& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvariable y;
  y=K/(1.0+(K/n0-1.0)*exp(-r*t)); 

  RETURN_ARRAYS_DECREMENT();
  return (y);
}
dvar_vector logisticK( const dvector& t,  const prevariable& K,  const prevariable& r,  const prevariable& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=K/(1.0+(K/n0-1.0)*exp(-r*t)); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
dvar_vector logisticK( const dvector& t,  const dvar_vector& K,  const prevariable& r,  const prevariable& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=elem_div(K, 1.0 + elem_prod(K/n0-1.0, exp(-r*t))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
/*---------------------------------------------2nd variable is a vector*/
dvar_vector logisticK( const dvector& t,  const prevariable& K,  const dvar_vector& r,  const prevariable& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=K/(1.0+(K/n0-1.0)*exp(-1.0*elem_prod(r,t))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
dvar_vector logisticK( const dvector& t,  const dvar_vector& K,  const dvar_vector& r,  const prevariable& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=elem_div(K, 1.0 + elem_prod(K/n0-1.0, exp(-1.0*elem_prod(r,t)))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
/*---------------------------------------------------------3rd variable is a vector*/
/*---------------------------------------------2nd variable is a scalar*/
dvar_vector logisticK( const dvector& t,  const prevariable& K,  const prevariable& r,  const dvar_vector& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=K/(1.0+elem_prod((K/n0-1.0), exp(-r*t))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
dvar_vector logisticK( const dvector& t,  const dvar_vector& K,  const prevariable& r,  const dvar_vector& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=elem_div(K, 1.0 + elem_prod(elem_div(K, n0)-1.0, exp(-r*t))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
/*---------------------------------------------2nd variable is a vector*/
dvar_vector logisticK( const dvector& t,  const prevariable& K,  const dvar_vector& r,  const dvar_vector& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=K/(1.0+elem_prod(K/n0-1.0, exp(-1.0*elem_prod(r,t)))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
dvar_vector logisticK( const dvector& t,  const dvar_vector& K,  const dvar_vector& r,  const dvar_vector& n0)
{
    RETURN_ARRAYS_INCREMENT();  
  dvar_vector y;
  y=elem_div(K, 1.0 + elem_prod(elem_div(K, n0)-1.0, exp(-1.0*elem_prod(r,t)))); 

  RETURN_ARRAYS_DECREMENT();  
    return (y);
}
/*---------------------------------------------------------3rd variable is a scalar in a random effects model*/
/*---------------------------------------------2nd variable is a scalar in a random effects model*/
/*----------------------1st varible contains random effects*/
df1b2variable logisticK( const double& t,  const df1b2variable& K,  const df1b2variable& r,  const df1b2variable& n0)
{
  df1b2variable y;
  y=K/(1.0+(K/n0-1.0)*exp(-r*t)); 

    return (y);
}
df1b2vector logisticK( const dvector& t,  const df1b2variable& K,  const df1b2variable& r,  const df1b2variable& n0)
{
  df1b2vector y;
  y=K/(1.0+(K/n0-1.0)*exp(-r*t)); 

    return(y);
}
df1b2vector logisticK( const dvector& t,  const df1b2vector& K,  const df1b2variable& r,  const df1b2variable& n0)
{
  df1b2vector y;
  y=elem_div(K, 1.0 + elem_prod(K/n0-1.0, exp(-r*t))); 

    return(y);
}

/*---------------------------------------------2nd variable is a vector in a random effects model*/
/*----------------------1st varible contains random effects*/
df1b2vector logisticK( const dvector& t,  const df1b2variable& K,  const df1b2vector& r,  const df1b2variable& n0)
{
  df1b2vector y;
  y=K/(1.0+(K/n0-1.0)*exp(-1.0*elem_prod(r,t))); 

    return(y);
}
df1b2vector logisticK( const dvector& t,  const df1b2vector& K,  const df1b2vector& r,  const df1b2variable& n0)
{
  df1b2vector y;
  y=elem_div(K, 1.0 + elem_prod(K/n0-1.0, exp(-1.0*elem_prod(r,t)))); 

    return(y);
}


/*---------------------------------------------------------3rd variable is a vector in a random effects model*/
/*---------------------------------------------2nd variable is a scalar in a random effects model*/
/*----------------------1st varible contains random effects*/
df1b2vector logisticK( const dvector& t,  const df1b2variable& K,  const df1b2variable& r,  const df1b2vector& n0)
{
  df1b2vector y;
  y=K/(1.0+elem_prod((K/n0-1.0), exp(-r*t))); 

    return(y);
}
df1b2vector logisticK( const dvector& t,  const df1b2vector& K,  const df1b2variable& r,  const df1b2vector& n0)
{
  df1b2vector y;
  y=elem_div(K, 1.0 + elem_prod(elem_div(K, n0)-1.0, exp(-r*t))); 

    return(y);
}

/*---------------------------------------------2nd variable is a vector in a random effects model*/
/*----------------------1st varible contains random effects*/
df1b2vector logisticK( const dvector& t,  const df1b2variable& K,  const df1b2vector& r,  const df1b2vector& n0)
{
  df1b2vector y;
  y=K/(1.0+elem_prod(K/n0-1.0, exp(-1.0*elem_prod(r,t)))); 

    return(y);
}
df1b2vector logisticK( const dvector& t,  const df1b2vector& K,  const df1b2vector& r,  const df1b2vector& n0)
{
  df1b2vector y;
  y=elem_div(K, 1.0 + elem_prod(elem_div(K, n0)-1.0, exp(-1.0*elem_prod(r,t)))); 

    return(y);
}