Classes | |
| class | ArraySampleGenerator |
| Sequentially returns the elements of an array. More... | |
| class | Bootstrap< SampleGenerator > |
| Implementation of the Bootstrap error estimation method. More... | |
| class | Jacknife< SampleGenerator > |
| Implements the Jacknifing method of error estimation. More... | |
| class | MTSampleGenerator |
| Generate random elements of a calculated quantity for MT impedance data. More... | |
| class | StatErrEst< SampleGenerator > |
| This class is used as a base for stochastic error estimation. More... | |
Functions | |
| template<typename UblasMatrix> | |
| UblasMatrix | Cov (const UblasMatrix &observations) |
| Calculate the NxN covariance matrix for a NxM matrix of observations with 0 mean. | |
| template<typename UblasMatrix> | |
| void | PCA (const UblasMatrix &observations, gplib::cmat &evectors, gplib::cvec &evalues) |
| gplib::cmat | WhiteMat (gplib::cmat &evectors, gplib::cvec &evalues) |
| Calculate the Whitening Matrix. | |
| gplib::cmat | DeWhiteMat (gplib::cmat &evectors, gplib::cvec &evalues) |
| Calculate the Dewhitening Matrix. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | Mean (InputIterator begin, InputIterator end) |
| Calculate the mean for a given range. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | Variance (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Variance and give the mean as a third input parameter. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | Variance (InputIterator begin, InputIterator end) |
| Calculate the Variance for a given range when the mean is not known and has to be calculated as well. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | MeanErr (InputIterator begin, InputIterator end) |
| Calculate the Mean Error for a given input range. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | MeanErr (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Mean Error for a given input range when the mean is known and passed as a third parameter. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | StdDev (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Standard deviation with a given mean. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | StdDev (InputIterator begin, InputIterator end) |
| Calculate the Standard Deviation. | |
| template<typename InputIterator> | |
| void | SubMean (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mean) |
| Substract the mean from each element in the container, mean is passed as a parameter. | |
| template<typename InputIterator> | |
| void | SubMean (InputIterator begin, InputIterator end) |
| Substract the mean from each element in the container, mean is calculated. | |
| template<typename InputIterator> | |
| std::iterator_traits < InputIterator >::value_type | Median (InputIterator begin, InputIterator end) |
| Calculate the median for a vector style container. | |
| UblasMatrix Cov | ( | const UblasMatrix & | observations | ) | [inline] |
| gplib::cmat DeWhiteMat | ( | gplib::cmat & | evectors, | |
| gplib::cvec & | evalues | |||
| ) |
| std::iterator_traits<InputIterator>::value_type Mean | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
Calculate the mean for a given range.
/file This header contains some simple statistical routines. All all templates for widest possible use
Definition at line 18 of file statutils.h.
Referenced by GeneralGA::DoIteration(), main(), MeanErr(), StdDev(), SubMean(), and Variance().
| std::iterator_traits<InputIterator>::value_type MeanErr | ( | InputIterator | begin, | |
| InputIterator | end, | |||
| typename std::iterator_traits< InputIterator >::value_type | mv | |||
| ) | [inline] |
Calculate the Mean Error for a given input range when the mean is known and passed as a third parameter.
Definition at line 52 of file statutils.h.
References Variance().
| std::iterator_traits<InputIterator>::value_type MeanErr | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
Calculate the Mean Error for a given input range.
Definition at line 45 of file statutils.h.
References Mean().
Referenced by main().
| std::iterator_traits<InputIterator>::value_type Median | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
Calculate the median for a vector style container.
Definition at line 90 of file statutils.h.
Referenced by main().
| void PCA | ( | const UblasMatrix & | observations, | |
| gplib::cmat & | evectors, | |||
| gplib::cvec & | evalues | |||
| ) | [inline] |
/file This file contains function connected to Principal Component Analysis
! This template function calculates the principal component rotation matrix from a matrix of observations
/*! The input matrix observations has the different channels (or datasets) as rows and corresponding samples as columns the parameter pcatrans will contain the matrix of principal component vectors, at the moment in no particular order
Definition at line 22 of file PCA.h.
Referenced by ComplexICA(), FastICA(), and main().
| std::iterator_traits<InputIterator>::value_type StdDev | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
| std::iterator_traits<InputIterator>::value_type StdDev | ( | InputIterator | begin, | |
| InputIterator | end, | |||
| typename std::iterator_traits< InputIterator >::value_type | mv | |||
| ) | [inline] |
Calculate the Standard deviation with a given mean.
Definition at line 59 of file statutils.h.
References Variance().
| void SubMean | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
Substract the mean from each element in the container, mean is calculated.
Definition at line 82 of file statutils.h.
| void SubMean | ( | InputIterator | begin, | |
| InputIterator | end, | |||
| typename std::iterator_traits< InputIterator >::value_type | mean | |||
| ) | [inline] |
Substract the mean from each element in the container, mean is passed as a parameter.
Definition at line 75 of file statutils.h.
Referenced by main(), RemoveSpike(), ShortCorr(), StackedSpectrum(), SubMean(), and TimeFrequency().
| std::iterator_traits<InputIterator>::value_type Variance | ( | InputIterator | begin, | |
| InputIterator | end | |||
| ) | [inline] |
Calculate the Variance for a given range when the mean is not known and has to be calculated as well.
Definition at line 36 of file statutils.h.
References Mean(), and Variance().
| std::iterator_traits<InputIterator>::value_type Variance | ( | InputIterator | begin, | |
| InputIterator | end, | |||
| typename std::iterator_traits< InputIterator >::value_type | mv | |||
| ) | [inline] |
Calculate the Variance and give the mean as a third input parameter.
Definition at line 26 of file statutils.h.
Referenced by main(), MeanErr(), StdDev(), and Variance().
| gplib::cmat WhiteMat | ( | gplib::cmat & | evectors, | |
| gplib::cvec & | evalues | |||
| ) |
Calculate the Whitening Matrix.
Given the complex matrix of eigenvectors evectors and the complex vector of eigenvalues as calculated by PCA, calculate the Whitening Matrix and return it
Definition at line 41 of file PCA.h.
Referenced by ComplexICA(), FastICA(), and main().
1.5.5