Changeset 3614


Ignore:
Timestamp:
Feb 6, 2017, 2:37:33 AM (6 years ago)
Author:
Peter
Message:

refs #867 and #882. Interface for Negative Binomiual and Poisson regression

Location:
trunk/yat/regression
Files:
4 added
2 edited

Legend:

Unmodified
Added
Removed
  • trunk/yat/regression/Makefile.am

    r2932 r3614  
    2929  yat/regression/LinearInterpolation.cc yat/regression/LinearWeighted.cc  \
    3030  yat/regression/Local.cc yat/regression/MultiDimensional.cc \
    31   yat/regression/MultiDimensionalWeighted.cc yat/regression/Naive.cc    \
     31  yat/regression/MultiDimensionalWeighted.cc \
     32  yat/regression/Multivariate.cc \
     33  yat/regression/Naive.cc   \
    3234  yat/regression/NaiveWeighted.cc yat/regression/OneDimensional.cc \
    3335  yat/regression/OneDimensionalWeighted.cc        \
     
    5153  $(srcdir)/yat/regression/MultiDimensional.h \
    5254  $(srcdir)/yat/regression/MultiDimensionalWeighted.h \
     55  $(srcdir)/yat/regression/Multivariate.h \
    5356  $(srcdir)/yat/regression/Naive.h \
    5457  $(srcdir)/yat/regression/NaiveWeighted.h \
     58  $(srcdir)/yat/regression/NegativeBinomial.h \
    5559  $(srcdir)/yat/regression/OneDimensional.h \
    5660  $(srcdir)/yat/regression/OneDimensionalWeighted.h \
     
    5862  $(srcdir)/yat/regression/PolynomialInterpolation.h \
    5963  $(srcdir)/yat/regression/PolynomialWeighted.h \
     64  $(srcdir)/yat/regression/Poisson.h \
    6065  $(srcdir)/yat/regression/TukeyBiweight.h
  • trunk/yat/regression/MultiDimensional.h

    r3611 r3614  
    55
    66/*
    7   Copyright (C) 2005, 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
    87  Copyright (C) 2009 Peter Johansson
    98
     
    2423*/
    2524
     25#include "Multivariate.h"
     26
    2627#include "yat/utility/Matrix.h"
    2728#include "yat/utility/Vector.h"
     
    3334namespace regression {
    3435
    35   ///
    36   /// @brief MultiDimesional fitting.
    37   ///
    38   class MultiDimensional
     36  /**
     37     \brief Linear MultiDimesional regression
     38  */
     39  class MultiDimensional : public Multivariate
    3940  {
    4041  public:
     
    5354       \brief covariance of parameters
    5455
    55        The covariance of fit parameters are calculated as \f$ \sigma^2
    56        (X'X)^{-1} \f$ where \f$ \sigma^2 \f$ is the variance of the of
    57        the error terms.
     56       The covariance of fit parameters is calculated as \f$ \sigma^2
     57       (X'X)^{-1} \f$ where \f$ \sigma^2\f$ is the variance of error
     58       residuals.
    5859    */
    5960    const utility::Matrix& covariance(void) const;
Note: See TracChangeset for help on using the changeset viewer.