10 #ifndef __LINEARTIMEMMD_H_
11 #define __LINEARTIMEMMD_H_
15 #include <shogun/lib/external/libqp.h>
20 class CStreamingFeatures;
189 bool multiple_kernels=
false);
244 return "LinearTimeMMD";
void set_blocksize(index_t blocksize)
CStreamingFeatures * m_streaming_p
virtual void compute_statistic_and_Q(SGVector< float64_t > &statistic, SGMatrix< float64_t > &Q)
virtual EStatisticType get_statistic_type() const
virtual CFeatures * get_p_and_q()
void set_simulate_h0(bool simulate_h0)
virtual void compute_statistic_and_variance(SGVector< float64_t > &statistic, SGVector< float64_t > &variance, bool multiple_kernels=false)
virtual ~CLinearTimeMMD()
virtual float64_t compute_threshold(float64_t alpha)
CStreamingFeatures * m_streaming_q
virtual float64_t perform_test()
virtual void set_p_and_q(CFeatures *p_and_q)
virtual float64_t compute_variance_estimate()
Two sample test base class. Provides an interface for performing a two-sample test, i.e. Given samples from two distributions and , the null-hypothesis is: , the alternative hypothesis: .
virtual const char * get_name() const
The class Features is the base class of all feature objects.
Streaming features are features which are used for online algorithms.
This class implements the linear time Maximum Mean Statistic as described in [1]. This statistic is i...
virtual CStreamingFeatures * get_streaming_q()
virtual CStreamingFeatures * get_streaming_p()
virtual SGVector< float64_t > bootstrap_null()
virtual float64_t compute_p_value(float64_t statistic)
virtual float64_t compute_statistic()