CNConfidence -- Evaluation with Confidence Intervals

SYNOPSIS

#include <CNCL/Confidence.h>

TYPE

CN_CONFIDENCE

BASE CLASSES

CNStatistics

DERIVED CLASSES

None

RELATED CLASSES

CNMoments CNMomentsTime

DESCRIPTION

The CNConfidence class yields the moments of an input sequence:

• mean,
• variance and relative variance (squared coefficient of variation),
• 2nd and 3rd zero moment,
• 3rd central moment,
• deviation and relative deviation (coefficient of variation),
• skewness.

Constructors:

CNConfidence(CNParam *param)

CNConfidence(const char* aName = NIL, const char* aDescription = NIL);

Initializes a CNConfidence evaluation. Optionally, you can specify aName and aDescription of the statistical evaluator.

In addition to the member functions required by CNCL and CNStatistics, CNConfidence provides:

virtual double mean() const;

Returns mean of the input values.

double variance() const;

Returns variance.

double M_2() const;

Returns 2nd moment.

double M_3() const;

Returns 3rd moment.

double Z_3() const;

Returns 3rd central moment.

double skewness() const;

Returns skewness.

double relative_variance() const;

Returns relative variance (squared coefficient of variation).

double relative_deviation() const;

Returns relative deviation (coefficient of variation).

double z_level(double conf) const;

Returns Z-level (argument) of error function for given confidence level (inverse error function).

double err_level(double z_level) const;

Returns value of error function to given (Z-level) argument.

double conf_level(double z_level) const;

Returns value of confidence probability to given (Z-level) argument.

double low_conf_bound(double conf) const;

Returns lower confidence boundary to given confidence level. The estimator is determined by mean().

double hi_conf_bound(double conf) const;

Returns upper confidence boundary to given confidence level. The estimator is determined by mean().

In general the confidence level conf = 0.95 is quite useful. It means that in 1 out of 20 measurements the "true" value is within the confidence interval determined by hi_conf_bound() and low_conf_bound().

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