/usr/include/shogun/statistics/TestStatistic.h is in libshogun-dev 3.2.0-7.3build4.
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* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2012-2013 Heiko Strathmann
*/
#ifndef __TESTSTATISTIC_H_
#define __TESTSTATISTIC_H_
#include <shogun/base/SGObject.h>
namespace shogun
{
/** enum for different statistic types */
enum EStatisticType
{
S_LINEAR_TIME_MMD, S_QUADRATIC_TIME_MMD, S_HSIC
};
/** enum for different method to approximate null-distibution */
enum ENullApproximationMethod
{
BOOTSTRAP, MMD2_SPECTRUM, MMD2_GAMMA, MMD1_GAUSSIAN, HSIC_GAMMA
};
/** @brief Test statistic base class. Provides an interface for statistical
* tests via three methods: compute_statistic(), compute_p_value() and
* compute_threshold(). The second computes a p-value for the statistic computed
* by the first method.
* The p-value represents the position of the statistic in the null-distribution,
* i.e. the distribution of the statistic population given the null-hypothesis
* is true. (1-position = p-value).
* The third method, compute_threshold(), computes a threshold for a given
* test level which is needed to reject the null-hypothesis.
*
* Also provides an interface for sampling from the null-distribution.
* The actual sampling has to be implemented in sub-classes.
*
* All statistical tests should inherit from this class.
*
* Abstract base class.
*/
class CTestStatistic : public CSGObject
{
public:
CTestStatistic();
virtual ~CTestStatistic();
/** @return test statistic for the given data/parameters/methods */
virtual float64_t compute_statistic()=0;
/** computes a p-value based on current method for approximating the
* null-distribution. The p-value is the 1-p quantile of the null-
* distribution where the given statistic lies in.
* This method should be overridden for different implementations
*
* @param statistic statistic value to compute the p-value for
* @return p-value parameter statistic is the (1-p) percentile of the
* null distribution
*/
virtual float64_t compute_p_value(float64_t statistic)=0;
/** computes a threshold based on current method for approximating the
* null-distribution. The threshold is the value that a statistic has
* to have in ordner to reject the null-hypothesis.
* This method should be overridden for different implementations
*
* @param alpha test level to reject null-hypothesis
* @return threshold for statistics to reject null-hypothesis
*/
virtual float64_t compute_threshold(float64_t alpha)=0;
/** Performs the complete two-sample test on current data and returns a
* p-value.
*
* This is a wrapper that calls compute_statistic first and then
* calls compute_p_value using the obtained statistic. In some statistic
* classes, it might be possible to compute statistic and p-value in
* one single run which is more efficient. Therefore, this method might
* be overwritten in subclasses.
*
* The method for computing the p-value can be set via
* set_null_approximation_method().
*
* @return p-value such that computed statistic is the (1-p) quantile
* of the estimated null distribution
*/
virtual float64_t perform_test();
/** Performs the complete two-sample test on current data and returns
* a binary answer wheter null hypothesis is rejected or not.
*
* This is just a wrapper for the above perform_test() method that
* returns a p-value. If this p-value lies below the test level alpha,
* the null hypothesis is rejected.
*
* Should not be overwritten in subclasses. (Therefore not virtual)
*
* @param alpha test level alpha.
* @return true if null hypothesis is rejected and false otherwise
*/
bool perform_test(float64_t alpha);
/** merges both sets of samples and computes the test statistic
* m_bootstrap_iteration times
*
* @return vector of all statistics
*/
virtual SGVector<float64_t> bootstrap_null()=0;
/** sets the number of bootstrap iterations for bootstrap_null()
*
* @param bootstrap_iterations how often bootstrapping shall be done
*/
virtual void set_bootstrap_iterations(index_t bootstrap_iterations);
/** sets the method how to approximate the null-distribution
* @param null_approximation_method method to use
*/
virtual void set_null_approximation_method(
ENullApproximationMethod null_approximation_method);
/** returns the statistic type of this test statistic */
virtual EStatisticType get_statistic_type() const=0;
virtual const char* get_name() const=0;
private:
void init();
protected:
/** number of iterations for bootstrapping null-distributions */
index_t m_bootstrap_iterations;
/** Defines how the the null distribution is approximated */
ENullApproximationMethod m_null_approximation_method;
};
}
#endif /* __TESTSTATISTIC_H_ */
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