Class Statistics

Contains a number of statistic functions.

Inheritance

object

Statistics

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: TheXDS.MCART.Math

Assembly: MCART.dll

Syntax

public static class Statistics

Methods

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AbsoluteDeviation(IEnumerable<double>, in double)

Calculates the absolute deviation of a point in a data set.

Declaration

public static double AbsoluteDeviation(this IEnumerable<double> data, in double point)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the absolute deviation.
double	point	Point for which to calculate the absolute deviation.

Returns

Type	Description
double	The absolute deviation of the point in a data set.

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Average(in double, in int, in double)

Gets a new average value from the specified parameters.

Declaration

public static double Average(this in double value, in int samples, in double oldAverage)

Parameters

Type	Name	Description
double	value	New value to add to the average.
int	samples	Number of samples of the previous average.
double	oldAverage	Previous average.

Returns

Type	Description
double	A new average that includes `value`.

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Correlation(IEnumerable<double>, IEnumerable<double>)

Calculates the level of correlation between two data sets.

Declaration

public static double Correlation(IEnumerable<double> dataA, IEnumerable<double> dataB)

Parameters

Type	Name	Description
IEnumerable<double>	dataA	First data set.
IEnumerable<double>	dataB	Second data set.

Returns

Type	Description
double	`1.0` for maximum correlation, `0.0` for minimum correlation.

Exceptions

Type	Condition
IndexOutOfRangeException	Thrown if either set has a different quantity of elements with respect to the other.

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Covariance(IEnumerable<double>, IEnumerable<double>)

Calculates the covariance between two data sets.

Declaration

public static double Covariance(IEnumerable<double> dataA, IEnumerable<double> dataB)

Parameters

Type	Name	Description
IEnumerable<double>	dataA	First data set.
IEnumerable<double>	dataB	Second data set.

Returns

Type	Description
double	`1.0` for maximum covariance, `0.0` for minimum covariance.

Exceptions

Type	Condition
IndexOutOfRangeException	Thrown if either set has a different quantity of elements with respect to the other.

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DeviationSquared(IEnumerable<double>)

Calculates the squared deviation of a data set.

Declaration

public static double DeviationSquared(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the squared deviation.

Returns

Type	Description
double	The squared deviation of a data set.

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Fisher(in double)

Applies the Fisher transformation to a discrete value.

Declaration

public static double Fisher(this in double value)

Parameters

Type	Name	Description
double	value	Value to which to apply the Fisher transformation.

Returns

Type	Description
double	The result of the Fisher transformation of the specified value.

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Forecast(in double, IEnumerable<double>, IEnumerable<double>)

Given the value valueA in the set dataA, predicts the resulting value with the set dataB.

Declaration

public static double Forecast(in double valueA, IEnumerable<double> dataA, IEnumerable<double> dataB)

Parameters

Type	Name	Description
double	valueA	Output value of the set `dataA`.
IEnumerable<double>	dataA	Data set that produced `valueA`.
IEnumerable<double>	dataB	Data set with which to perform the prediction.

Returns

Type	Description
double	The prediction of the output value given the set `dataB`.

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GeometricMean(IEnumerable<double>)

Calculates the geometric tendency of a data set.

Declaration

public static double GeometricMean(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the geometric tendency.

Returns

Type	Description
double	The geometric tendency of a data set.

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HarmonicMean(IEnumerable<double>)

Calculates the harmonic tendency of a data set.

Declaration

public static double HarmonicMean(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the harmonic tendency.

Returns

Type	Description
double	The harmonic tendency of a data set.

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MeanAbsoluteDeviation(IEnumerable<double>)

Calculates the mean absolute deviation of a data set.

Declaration

public static double MeanAbsoluteDeviation(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the mean absolute deviation.

Returns

Type	Description
double	The mean absolute deviation of a data set.

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MeanTendency(IEnumerable<double>)

Calculates the mean tendency of a data set.

Declaration

public static double MeanTendency(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the mean tendency.

Returns

Type	Description
double	The mean tendency of a data set.

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Median(IEnumerable<double>)

Calculates the median of a data set.

Declaration

public static double Median(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the median.

Returns

Type	Description
double	The median of a data set.

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MedianAbsoluteDeviation(IEnumerable<double>)

Calculates the median absolute deviation of a data set.

Declaration

public static double MedianAbsoluteDeviation(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the median absolute deviation.

Returns

Type	Description
double	The median absolute deviation of a data set.

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Mode(IEnumerable<double>)

Calculates the mode of a data set.

Declaration

public static IEnumerable<double> Mode(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the mode.

Returns

Type	Description
IEnumerable<double>	The mode of a data set.

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Normalize(IEnumerable<double>, double)

Gets a normalized range for a given data set, given an error margin.

Declaration

public static IEnumerable<Range<double>> Normalize(this IEnumerable<double> data, double errorMargin)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set to normalize.
double	errorMargin	Error margin tolerated.

Returns

Type	Description
IEnumerable<Range<double>>	An enumeration with the normalized values of the data set according to an error margin value.

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StandardDeviation(IEnumerable<double>)

Gets the standard deviation of a data set.

Declaration

public static double StandardDeviation(this IEnumerable<double> data)

Parameters

Type	Name	Description
IEnumerable<double>	data	Data set for which to calculate the standard deviation.

Returns

Type	Description
double	The standard deviation of a data set.

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Variate(in double, in double)

Varies a value according to a percentage of its delta.

Declaration

public static double Variate(this in double value, in double delta)

Parameters

Type	Name	Description
double	value	Value to vary.
double	delta	Variance delta.

Returns

Type	Description
double	A value randomly varied according to a delta.