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* Scythe Statistical Library Copyright (C) 2000-2002 Andrew D. Martin
* and Kevin M. Quinn; 2002-present Andrew D. Martin, Kevin M. Quinn,
* and Daniel Pemstein. All Rights Reserved.
*
* This program is free software; you can redistribute it and/or
* modify under the terms of the GNU General Public License as
* published by Free Software Foundation; either version 2 of the
* License, or (at your option) any later version. See the text files
* COPYING and LICENSE, distributed with this source code, for further
* information.
* --------------------------------------------------------------------
* scythestat/stat.h
*
*/
/*!
* \file stat.h
* \brief Definitions for functions that perform common
* statistical operations on Scythe Matrix objects.
*
* \note As is the case throughout the library, we provide both
* general and default template definitions of the Matrix-returning
* functions in this file, explicitly providing documentation for only
* the general template versions.
*/
#ifndef SCYTHE_STAT_H
#define SCYTHE_STAT_H
#ifdef SCYTHE_COMPILE_DIRECT
#include "matrix.h"
#include "algorithm.h"
#include "error.h"
#else
#include "scythestat/matrix.h"
#include "scythestat/algorithm.h"
#include "scythestat/error.h"
#endif
#include <numeric>
#include <set>
namespace scythe {
namespace {
typedef unsigned int uint;
}
/* A macro for defining column versions of a function. That is,
* when expanded, this macro produces general and default template
* functions that compute function NAME on each column in a matrix and
* return a row vector with the results. We use this to generate
* column versions of every function in this header file.
*/
#define SCYTHE_STATMETH_COL(NAME) \
template <matrix_order RO, matrix_style RS, typename T, \
matrix_order PO, matrix_style PS> \
Matrix<T,RO,RS> \
NAME ## c (const Matrix<T,PO,PS>& A) \
{ \
Matrix<T,RO,RS> res (1, A.cols(), false); \
\
for (uint j = 0; j < A.cols(); ++j) \
res[j] = NAME(A(_, j)); \
\
return res; \
} \
\
template <typename T, matrix_order O, matrix_style S> \
Matrix<T,O,Concrete> \
NAME ## c (const Matrix<T,O,S>& A) \
{ \
return NAME ## c<O,Concrete>(A); \
}
/* Calculate the sum of a Matrix */
/*!
* \brief Calculate the sum of a Matrix
*
* This function calculates the sum of a matrix by adding each element
* in turn.
*
* \param A The matrix to be summed.
*
* \see prod(const Matrix<T,PO,PS> &A)
* \see sumc(const Matrix<T,PO,PS> &A)
* \see prodc(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
sum (const Matrix<T,PO,PS> &A)
{
return (std::accumulate(A.begin_f(), A.end_f(), (T) 0));
}
/* Calculate the sum of each column in a Matrix */
/*!
* \brief Calculate the sum of each column in a Matrix
*
* This function calculates the sum of each column in a matrix by
* consecutively adding elements in a single column, looping through all
* columns, and returning the results.
*
* \param A The matrix to be summed.
*
* \see prod(const Matrix<T,PO,PS> &A)
* \see sum(const Matrix<T,PO,PS> &A)
* \see prodc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(sum);
/* Calculate the product of a Matrix */
/*!
* \brief Calculate the product of a Matrix
*
* This function calculates the product of a matrix by beginning with the
* first element of a matrix, and consecutively multiplying each entry.
*
* \param A The matrix to be multiplied.
*
* \see sumc(const Matrix<T,PO,PS> &A)
* \see sum(const Matrix<T,PO,PS> &A)
* \see prodc(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
prod (const Matrix<T,PO,PS> &A)
{
return std::accumulate(A.begin_f(), A.end_f(), (T) 1,
std::multiplies<T> ());
}
/* Calculate the product of each column of a matrix */
/*!
* \brief Calculate the product of each column of a Matrix
*
* This function calculates the product of each column of a matrix by
* multiplying all elements of a single column, looping through all columns,
* and returning the results.
*
* \param A The matrix to be multiplied.
*
* \see sumc(const Matrix<T,PO,PS> &A)
* \see sum(const Matrix<T,PO,PS> &A)
* \see prod(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(prod);
/* Calculate the mean of a Matrix */
/*!
* \brief Calculate the mean of a Matrix
*
* This function calculates the mean of a matrix by summing all elements of
* the matrix, and dividing by the total number of elements in the matrix.
*
* \param A The matrix to be averaged.
*
* \see sum(const Matrix<T,PO,PS> &A)
* \see meanc(const Matrix<T,PO,PS> &A)
* \see median(const Matrix<T,PO,PS> &A)
* \see mode(const Matrix<T,PO,PS> &A)
* \see variance(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
mean (const Matrix<T,PO,PS> &A)
{
return (std::accumulate(A.begin_f(), A.end_f(), (T) 0) / A.size());
}
/* Calculate the mean of each column of a Matrix */
/*!
* \brief Calculate the mean of each column of a Matrix
*
* This function calculates the mean of each column of a matrix by summing
* all elements of a column in the matrix, divding by the total number of
* elements in the column, and looping over every column in the matrix.
*
* \param A The matrix to be averaged.
*
* \see sumc(const Matrix<T,PO,PS> &A)
* \see mean(const Matrix<T,PO,PS> &A)
* \see medianc(const Matrix<T,PO,PS> &A)
* \see modec(const Matrix<T,PO,PS> &A)
* \see variancec(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(mean);
/* Calculate the median of a matrix. Uses a sort but I'll implement
* the randomized alg when I figure out how to generalize it to
* even-length lists
*/
/*!
* \brief Calculate the median of a Matrix
*
* This function calculates the median of a matrix by first sorting the elements
* of the matrix, and then finding the middle element.
*
* \param A The matrix whose median is of interest.
*
* \see medianc(const Matrix<T,PO,PS> &A)
* \see mean(const Matrix<T,PO,PS> &A)
* \see mode(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
median (const Matrix<T,PO,PS> &A)
{
Matrix<T, PO, PS> temp(A);
uint n = temp.size();
sort(temp.begin(), temp.end());
if (n % 2 == 0)
return ((temp[n / 2] + temp[n / 2 - 1]) / 2);
else
return temp[(uint) ::floor(n / 2)];
}
/* Calculate the median of each column of a matrix */
/*!
* \brief Calculate the median of each column a Matrix
*
* This function calculates the median of each column of a matrix by first
* sorting the elements and locating the middle in a single column, and then
* looping over all columns.
*
* \param A The matrix whose medians are of interest.
*
* \see median(const Matrix<T,PO,PS> &A)
* \see meanc(const Matrix<T,PO,PS> &A)
* \see modec(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(median);
/* Calculate the mode of a matrix */
/*!
* \brief Calculate the mode of a Matrix
*
* This function calculates the mode of a matrix by determining which value of
* the matrix occurs with the highest frequency.
*
* \param A The matrix whose mode is of interest.
*
* \see modec(const Matrix<T,PO,PS> &A)
* \see mean(const Matrix<T,PO,PS> &A)
* \see median(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
mode (const Matrix<T,PO,PS> &A)
{
Matrix<T, PO, PS> temp(A);
sort(temp.begin(), temp.end());
T last = temp[0];
uint cnt = 1;
T cur_max = temp[0];
uint max_cnt = 1;
for (uint i = 1; i < temp.size(); ++i) {
if (last == temp[i]) {
++cnt;
} else {
last = temp[i];
cnt = 1;
}
if (cnt > max_cnt) {
max_cnt = cnt;
cur_max = temp[i];
}
}
return cur_max;
}
/*!
* \brief Calculate the mode of the columns of a Matrix
*
* This function calculates the mode of the columns of a matrix by
* determining which value in a single column of the matrix occurs
* most frequently, and then looping over all columns.
*
* \param A The matrix whose modes are of interest.
*
* \see mode(const Matrix<T,PO,PS> &A)
* \see meanc(const Matrix<T,PO,PS> &A)
* \see medianc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(mode);
/* Calculate the variance of a Matrix */
/* A functor that encapsulates a single variance calculation step.
* Also used by skew and kurtosis. */
namespace {
template <typename T, typename T2>
struct var_step : std::binary_function<T, T, T>
{
T constant_;
T2 divisor_;
T exponent_;
var_step (T c, T2 d, T e) : constant_ (c), divisor_ (d),
exponent_ (e) {}
T operator() (T last, T x) const
{
return (last + std::pow(constant_ - x, exponent_) / divisor_);
}
};
}
/*!
* \brief Calculate the variance of a Matrix
*
* This function calculates the variance of a matrix.
*
* \param A The matrix whose variance is of interest.
*
* \see var(cons Matrix<T,PO,PS> &A, T mu)
* \see varc(const Matrix<T,PO,PS> &A)
* \see sd(const Matrix<T,PO,PS> &A)
* \see mean(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
var (const Matrix<T,PO,PS> &A)
{
return var(A, mean(A));
}
/* Calculate the variances of each column of a Matrix. */
/*!
* \brief Calculate the variance of each column of a Matrix
*
* This function calculates the variance of each column of a matrix.
*
* \param A The matrix whose variances are of interest.
*
* \see var(const Matrix<T,PO,PS> &A)
* \see var(cons Matrix<T,PO,PS> &A, T mu)
* \see sdc(const Matrix<T,PO,PS> &A)
* \see meanc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(var);
/*!
* \brief Calculate the variance of a Matrix
*
* This function calculates the variance of a matrix when the mean is
* already known.
*
* \param A The matrix whose variance is of interest.
* \param mu The mean of the values in the matrix.
*
* \see var(cons Matrix<T,PO,PS> &A)
* \see varc(const Matrix<T,PO,PS> &A)
* \see sd(const Matrix<T,PO,PS> &A)
* \see mean(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
var (const Matrix<T,PO,PS> &A, T mu)
{
return std::accumulate(A.begin_f(), A.end_f(), (T) 0,
var_step<T, uint> (mu, A.size() - 1, 2));
}
/* Calculate the standard deviation of a Matrix (not std cause of namespace std:: */
/*!
* \brief Calculate the standard deviation of a Matrix
*
* This function calculates the standard deviation of a matrix by
* taking the square root of the matrix's variance.
*
* \param A The matrix whose standard deviation is of interest.
*
* \see sd(const Matrix<T,PO,PS) &A, T mu)
* \see sdc(const Matrix<T,PO,PS> &A)
* \see variance(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
sd (const Matrix<T,PO,PS> &A)
{
return std::sqrt(var(A));
}
/* Calculate the standard deviation of each column of a Matrix */
/*!
* \brief Calculate the standard deviation of each column of a Matrix
*
* This function calculates the standard deviation of each column of a matrix by
* taking the square root of each column's variance.
*
* \param A The matrix whose standard deviations are of interest.
*
* \see sd(const Matrix<T,PO,PS> &A)
* \see variancec(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(sd);
/*!
* \brief Calculate the standard deviation of a Matrix
*
* This function calculates the standard deviation of a matrix
* when the matrix's mean is already known.
*
* \param A The matrix whose standard deviation is of interest.
* \param mu The matrix mean.
*
* \see sd(const Matrix<T,PO,PS) &A)
* \see sdc(const Matrix<T,PO,PS> &A)
* \see variance(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
sd (const Matrix<T,PO,PS> &A, T mu)
{
return std::sqrt(var(A, mu));
}
/* Calculate the skew of a Matrix */
/*!
* \brief Calculate the skew of a Matrix
*
* This function calculates the skew of a matrix.
*
* \param A The matrix whose skew is of interest.
*
* \see skewc(const Matrix<T,PO,PS> &A)
* \see kurtosis(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
skew (const Matrix<T,PO,PS> &A)
{
T mu = mean(A);
T sde = sd(A, mu);
return std::accumulate(A.begin_f(), A.end_f(), (T) 0,
var_step<T, T> (mu, A.size() * std::pow(sde, 3), 3));
}
/* Calculate the skew of each column of a Matrix. */
/*!
* \brief Calculate the skew of each column of a Matrix
*
* This function calculates the skew of each column of a matrix.
*
* \param A The matrix whose skews are of interest.
*
* \see skew(const Matrix<T,PO,PS> &A)
* \see kurtosisc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(skew);
/* Calculate the kurtosis of a Matrix */
/*!
* \brief Calculate the kurtosis of a Matrix
*
* This function calculates the kurtosis of a matrix.
*
* \param A The matrix whose kurtosis is of interest.
*
* \see skew(const Matrix<T,PO,PS> &A)
* \see kurtosisc(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
kurtosis (const Matrix<T,PO,PS> &A)
{
T mu = mean(A);
T sde = sd(A, mu);
return (std::accumulate(A.begin_f(), A.end_f(), (T) 0,
var_step<T, T> (mu, A.size() * std::pow(sde, 4), 4))
- 3);
}
/* Calculate the kurtosis of each column of a Matrix. */
/*!
* \brief Calculate the kurtosis of each column of a Matrix
*
* This function calculates the kurtosis of each column of a matrix.
*
* \param A The matrix whose kurtoses are of interest.
*
* \see skewc(const Matrix<T,PO,PS> &A)
* \see kurtosis(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(kurtosis);
/* Calculates the maximum element in a Matrix */
/*!
* \brief Calculate the maximum element in a Matrix
*
* This function identifies the maximum element in a matrix.
*
* \param A The matrix whose maximum element is of interest.
*
* \see min(const Matrix<T,PO,PS> &A)
* \see maxc (const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
max (const Matrix<T,PO,PS> &A)
{
return *(max_element(A.begin_f(), A.end_f()));
}
/*!
* \brief Calculate the maximum of each column of a Matrix
*
* This function identifies the maximum of each column in a matrix.
*
* \param A The matrix whose maximae are of interest.
*
* \see max(const Matrix<T,PO,PS> &A)
* \see minc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(max);
/* Calculates the minimum element in a Matrix */
/*!
* \brief Calculate the maximum element in a Matrix
*
* This function identifies the maximum element in a matrix.
*
* \param A The matrix whose maximum element is of interest.
*
* \see max(const Matrix<T,PO,PS> &A)
* \see minc(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
T
min (const Matrix<T,PO,PS> &A)
{
return *(min_element(A.begin_f(), A.end_f()));
}
/*!
* \brief Calculate the minimum of each column of a Matrix
*
* This function identifies the minimum of each column in a matrix.
*
* \param A The matrix whose minimae are of interest.
*
* \see min(const Matrix<T,PO,PS> &A)
* \see maxc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(min);
/* Find the index of the max element */
/*!
* \brief Calculate the index of the maximum element in a Matrix
*
* This function identifies the index of the maximum element in a matrix.
*
* \param A The matrix whose maximum element indices are of interest.
*
* \see minind(const Matrix<T,PO,PS> &A)
* \see max(const Matrix<T,PO,PS> &A)
* \see maxindc(const Matrix<T,PO,PS> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
unsigned int
maxind (const Matrix<T,PO,PS> &A)
{
return (max_element(A.begin_f(), A.end_f())).get_index();
}
/*!
* \brief Calculate the index of the maximum for each column of a Matrix
*
* This function identifies the index of the maximum for each column of a Matrix.
*
* \param A The matrix whose maximum indices are of interest.
*
* \see maxc(const Matrix<T,PO,PS> &A)
* \see minindc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(maxind);
/* Find the index of the min element */
/*!
* \brief Calculate the index of the minimum element in a Matrix
*
* This function identifies the index of the minimum element in a matrix.
*
* \param A The matrix whose minimum element indices are of interest.
*
* \see maxind(const Matrix<T,PO,PS> &A)
* \see min(const Matrix<T,PO,PS> &A)
* \see minindc(const Matrix <T> &A)
*/
template <typename T, matrix_order PO, matrix_style PS>
unsigned int
minind (const Matrix<T,PO,PS> &A)
{
return (min_element(A.begin_f(), A.end_f())).get_index();
}
/*!
* \brief Calculate the index of the minimum for each column of a Matrix
*
* This function identifies the index of the minimum for each column of a Matrix.
*
* \param A The matrix whose minimum indices are of interest.
*
* \see minc(const Matrix<T,PO,PS> &A)
* \see maxindc(const Matrix<T,PO,PS> &A)
*/
SCYTHE_STATMETH_COL(minind);
} // end namespace scythe
#endif /* SCYTHE_STAT_H */
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