# Statistic Module

## Classes

class  imaging::LinearPca
Linear principal component analysis. More...

## Functions

void imaging::mean (const ublas::matrix< float_t > &data, ublas::vector< float_t > &result)
void imaging::var (const ublas::matrix< float_t > &data, ublas::vector< float_t > &result)
float_t imaging::mean (const ublas::vector< float_t > &data)
float_t imaging::var (const ublas::vector< float_t > &data)

## Detailed Description

The statistics module is a utility module which contains utility functions to compute means and variances. Additionally it includes an implementation of the linear principal component analysis (PCA).

## Function Documentation

 float_t imaging::mean ( const ublas::vector< float_t > & data )

`#include <statistic/utilities.hpp>`

Returns the mean of data.

 void imaging::mean ( const ublas::matrix< float_t > & data, ublas::vector< float_t > & result )

`#include <statistic/utilities.hpp>`

Computes the mean of each column of data and writes it to result. The vector result is resized to the number of columns of data upon return.

Referenced by imaging::var().

 float_t imaging::var ( const ublas::vector< float_t > & data )

`#include <statistic/utilities.hpp>`

Returns the variance data.

References imaging::mean(), and imaging::square().

 void imaging::var ( const ublas::matrix< float_t > & data, ublas::vector< float_t > & result )

`#include <statistic/utilities.hpp>`

Computes the variances of the columns of data and writes them to result. The vector result is resized to the number of columns of data upon return.

References imaging::mean(), and imaging::square().

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