Public Member Functions | Static Public Member Functions

polyCore Class Reference

polynomial Core as used for the weibull function More...

#include <core.h>

Inheritance diagram for polyCore:
PsiCore

List of all members.

Public Member Functions

 polyCore (const PsiData *data=NULL, const int sigmoid=1, const double alpha=0.1)
 construcor
 polyCore (const polyCore &original)
 copy constructor
double g (double x, const std::vector< double > &prm) const
 evaluate the polyCore
double dg (double x, const std::vector< double > &prm, int i) const
 derivative of the polyCore with respect to a parameter
double dgx (double x, const std::vector< double > &prm) const
 evaluate the first derivative of the core with respect to stimulus intensity
double ddg (double x, const std::vector< double > &prm, int i, int j) const
 2nd derivative of the polyCore object with respect to parameters
double inv (double y, const std::vector< double > &prm) const
 inverse of the core
double dinv (double y, const std::vector< double > &prm, int i) const
 derivative of the inverse core
std::vector< double > transform (int nprm, double a, double b) const
 transform the parameter from a logistic regression model to starting values
PsiCoreclone (void) const
 clone object by value

Static Public Member Functions

static std::string getDescriptor (void)
 get a short string that identifies the type of core

Detailed Description

polynomial Core as used for the weibull function

The classical weibull function is parameterized as 1-exp(-(x/alpha)^beta), this core defines the (x/alpha)^beta part in this parameterization. The PsiExponential sigmoid gives the 1-exp(-.) part.


Constructor & Destructor Documentation

polyCore::polyCore ( const PsiData data = NULL,
const int  sigmoid = 1,
const double  alpha = 0.1 
)

construcor

Parameters:
data use a data set to determine the correct scaling factors of initial values and initialize the objec
sigmoid ignored
alpha ignored

Member Function Documentation

double polyCore::ddg ( double  x,
const std::vector< double > &  prm,
int  i,
int  j 
) const [virtual]

2nd derivative of the polyCore object with respect to parameters

Parameters:
x stimulus intensity
prm parameter vector
i index of the first derivative parameter
j index of the 2nd derivatibe parameter

Reimplemented from PsiCore.

double polyCore::dg ( double  x,
const std::vector< double > &  prm,
int  i 
) const [virtual]

derivative of the polyCore with respect to a parameter

Parameters:
x stimulus intensity
prm parameter vector
i index of the parameter to which the derivative should be evaluated

Reimplemented from PsiCore.

double polyCore::dgx ( double  x,
const std::vector< double > &  prm 
) const [virtual]

evaluate the first derivative of the core with respect to stimulus intensity

Parameters:
x stimulus intensity
prm parameter vector

Reimplemented from PsiCore.

double polyCore::dinv ( double  y,
const std::vector< double > &  prm,
int  i 
) const [virtual]

derivative of the inverse core

Parameters:
y value at which to evaluate the inverse
prm parameter vector
i index of the parameter for which the derivative should be evaluated

Reimplemented from PsiCore.

double polyCore::g ( double  x,
const std::vector< double > &  prm 
) const [inline, virtual]

evaluate the polyCore

Parameters:
x stimulus intensity
prm parameter vector (alpha,beta, ...)

Reimplemented from PsiCore.

double polyCore::inv ( double  y,
const std::vector< double > &  prm 
) const [virtual]

inverse of the core

Parameters:
y value for which the core should be inverted
prm parameter vector

Reimplemented from PsiCore.

std::vector< double > polyCore::transform ( int  nprm,
double  a,
double  b 
) const [virtual]

transform the parameter from a logistic regression model to starting values

Parameters:
nprm number of parameters in the final model
a intercept of the logistic regression model
b slope of the logistic regression model to starting values

Reimplemented from PsiCore.


The documentation for this class was generated from the following files: