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CStatistics Class Reference

Detailed Description

Class that contains certain functions related to statistics, such as the student's t distribution.

Definition at line 27 of file Statistics.h.

Inheritance diagram for CStatistics:
Inheritance graph
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Public Member Functions

virtual const char * get_name () const
- Public Member Functions inherited from CSGObject
 CSGObject ()
 CSGObject (const CSGObject &orig)
virtual ~CSGObject ()
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGVector< char * > get_modelsel_names ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)

Static Public Member Functions

static float64_t mean (SGVector< float64_t > values)
static float64_t variance (SGVector< float64_t > values)
static float64_t std_deviation (SGVector< float64_t > values)
static float64_t confidence_intervals_mean (SGVector< float64_t > values, float64_t alpha, float64_t &conf_int_low, float64_t &conf_int_up)
static float64_t student_t_distribution (int32_t k, float64_t t)
static float64_t inverse_student_t_distribution (int32_t k, float64_t p)
static float64_t incomplete_beta (float64_t a, float64_t b, float64_t x)
static float64_t inverse_incomplete_beta (float64_t a, float64_t b, float64_t y)
static float64_t inverse_normal_distribution (float64_t y0)

Static Protected Member Functions

static float64_t ibetaf_incomplete_beta_ps (float64_t a, float64_t b, float64_t x, float64_t maxgam)
static float64_t ibetaf_incomplete_beta_fe (float64_t a, float64_t b, float64_t x, float64_t big, float64_t biginv)
static float64_t ibetaf_incomplete_beta_fe2 (float64_t a, float64_t b, float64_t x, float64_t big, float64_t biginv)

Additional Inherited Members

- Public Attributes inherited from CSGObject
SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
- Protected Member Functions inherited from CSGObject
virtual void load_serializable_pre () throw (ShogunException)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)

Member Function Documentation

float64_t confidence_intervals_mean ( SGVector< float64_t values,
float64_t  alpha,
float64_t conf_int_low,
float64_t conf_int_up 
)
static

Calculates the sample mean of a given set of samples and also computes the confidence interval for the actual mean for a given p-value, asuming that the actual variance and mean are unknown (These are estimated by the samples)

Only for normally distributed data

Parameters
valuesvector of values that are used for calculations
alphaactual mean lies in confidence interval with (1-alpha)*100%
conf_int_lowlower confidence interval border is written here
conf_int_upupper confidence interval border is written here
Returns
sample mean

Definition at line 52 of file Statistics.cpp.

virtual const char* get_name ( ) const
virtual
Returns
object name

Implements CSGObject.

Definition at line 135 of file Statistics.h.

float64_t ibetaf_incomplete_beta_fe ( float64_t  a,
float64_t  b,
float64_t  x,
float64_t  big,
float64_t  biginv 
)
staticprotected

Continued fraction expansion #1 for incomplete beta integral

Taken from ALGLIB under GPL2+

Definition at line 435 of file Statistics.cpp.

float64_t ibetaf_incomplete_beta_fe2 ( float64_t  a,
float64_t  b,
float64_t  x,
float64_t  big,
float64_t  biginv 
)
staticprotected

Continued fraction expansion #2 for incomplete beta integral

Taken from ALGLIB under GPL2+

Definition at line 331 of file Statistics.cpp.

float64_t ibetaf_incomplete_beta_ps ( float64_t  a,
float64_t  b,
float64_t  x,
float64_t  maxgam 
)
staticprotected

Power series for incomplete beta integral. Use when b*x is small and x not too close to 1.

Taken from ALGLIB under GPL2+

Definition at line 278 of file Statistics.cpp.

float64_t incomplete_beta ( float64_t  a,
float64_t  b,
float64_t  x 
)
static

Incomplete beta integral Returns incomplete beta integral of the arguments, evaluated from zero to x. The domain of definition is 0 <= x <= 1. In this implementation a and b are restricted to positive values. The integral is evaluated by a continued fraction expansion or, when b*x is small, by a power series.

Taken from ALGLIB under GPL2+

Definition at line 154 of file Statistics.cpp.

float64_t inverse_incomplete_beta ( float64_t  a,
float64_t  b,
float64_t  y 
)
static

Inverse of imcomplete beta integral Given y, the function finds x such that inverse_incomplete_beta(a, b, x) = y . The routine performs interval halving or Newton iterations to find the root of inverse_incomplete_beta(a, b, x)-y=0.

Taken from ALGLIB under GPL2+

Definition at line 581 of file Statistics.cpp.

float64_t inverse_normal_distribution ( float64_t  y0)
static

Inverse of Normal distribution function Returns the argument, x, for which the area under the Gaussian probability density function (integrated from minus infinity to x) is equal to y.

For small arguments 0 < y < exp(-2), the program computes z=sqrt(-2.0*log(y)) then the approximation is x=z-log(z)/z-(1/z)P(1/z)/Q(1/z). There are two rational functions P/Q, one for 0 < y < exp(-32) and the other for y up to exp(-2). For larger arguments, w = y - 0.5, and x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2)).

Taken from ALGLIB under GPL2+

Definition at line 1029 of file Statistics.cpp.

float64_t inverse_student_t_distribution ( int32_t  k,
float64_t  p 
)
static

Functional inverse of Student's t distribution Given probability p, finds the argument t such that stdtr(k,t) is equal to p.

Taken from ALGLIB under GPL2+

Definition at line 537 of file Statistics.cpp.

float64_t mean ( SGVector< float64_t values)
static

Calculates mean of given values

Parameters
valuesvector of values
Returns
variance of given values

Definition at line 21 of file Statistics.cpp.

float64_t std_deviation ( SGVector< float64_t values)
static

Calculates standard deviation of given values

Parameters
valuesvector of values
Returns
standard deviation of given values

Definition at line 47 of file Statistics.cpp.

float64_t student_t_distribution ( int32_t  k,
float64_t  t 
)
static

Student's t distribution Computes the integral from minus infinity to t of the Student For t < -2, this is the method of computation. For higher t, a direct method is derived from integration by parts. Since the function is symmetric about t=0, the area under the right tail of the density is found by calling the function with -t instead of t. Taken from ALGLIB under GPL2+

Parameters
kdegrees of freedom
tintegral is computed from minus infinity to t
Returns
described integral

Definition at line 79 of file Statistics.cpp.

float64_t variance ( SGVector< float64_t values)
static

Calculates variance of given values

Parameters
valuesvector of values
Returns
variance of given values

Definition at line 33 of file Statistics.cpp.


The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation