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StreamingStatistics Class

Statistics operating on an IEnumerable in a single pass, without keeping the full data in memory. Can be used in a streaming way, e.g. on large datasets not fitting into memory.
Inheritance Hierarchy
SystemObject
  Altaxo.Calc.StatisticsStreamingStatistics

Namespace: Altaxo.Calc.Statistics
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
Syntax
C#
public static class StreamingStatistics

The StreamingStatistics type exposes the following members.

Methods
 NameDescription
Public methodStatic memberCovariance(IEnumerableDouble, IEnumerableDouble) Estimates the unbiased population covariance from the provided two sample enumerable sequences, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public methodStatic memberCovariance(IEnumerableSingle, IEnumerableSingle) Estimates the unbiased population covariance from the provided two sample enumerable sequences, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public methodStatic memberEntropy Calculates the entropy of a stream of double values. Returns NaN if any of the values in the stream are NaN.
Public methodStatic memberGeometricMean(IEnumerableDouble) Evaluates the geometric mean of the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberGeometricMean(IEnumerableSingle) Evaluates the geometric mean of the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberHarmonicMean(IEnumerableDouble) Evaluates the harmonic mean of the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberHarmonicMean(IEnumerableSingle) Evaluates the harmonic mean of the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximum(IEnumerableDouble) Returns the largest value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximum(IEnumerableSingle) Returns the largest value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximumAbsolute(IEnumerableDouble) Returns the largest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximumAbsolute(IEnumerableSingle) Returns the largest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximumMagnitudePhase(IEnumerableComplex32) Returns the largest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMaximumMagnitudePhase(IEnumerableComplex) Returns the largest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMean(IEnumerableDouble) Estimates the arithmetic sample mean from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMean(IEnumerableSingle) Estimates the arithmetic sample mean from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMeanStandardDeviation(IEnumerableDouble) Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or any entry is NaN, and NaN for standard deviation if data has less than two entries or if any entry is NaN.
Public methodStatic memberMeanStandardDeviation(IEnumerableSingle) Estimates the arithmetic sample mean and the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or any entry is NaN, and NaN for standard deviation if data has less than two entries or if any entry is NaN.
Public methodStatic memberMeanVariance(IEnumerableDouble) Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or any entry is NaN, and NaN for variance if data has less than two entries or if any entry is NaN.
Public methodStatic memberMeanVariance(IEnumerableSingle) Estimates the arithmetic sample mean and the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN for mean if data is empty or any entry is NaN, and NaN for variance if data has less than two entries or if any entry is NaN.
Public methodStatic memberMinimum(IEnumerableDouble) Returns the smallest value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMinimum(IEnumerableSingle) Returns the smallest value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMinimumAbsolute(IEnumerableDouble) Returns the smallest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMinimumAbsolute(IEnumerableSingle) Returns the smallest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMinimumMagnitudePhase(IEnumerableComplex32) Returns the smallest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberMinimumMagnitudePhase(IEnumerableComplex) Returns the smallest absolute value from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberPopulationCovariance(IEnumerableDouble, IEnumerableDouble) Evaluates the population covariance from the full population provided as two enumerable sequences, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberPopulationCovariance(IEnumerableSingle, IEnumerableSingle) Evaluates the population covariance from the full population provided as two enumerable sequences, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberPopulationStandardDeviation(IEnumerableDouble) Evaluates the population standard deviation from the full population provided as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberPopulationStandardDeviation(IEnumerableSingle) Evaluates the population standard deviation from the full population provided as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberPopulationVariance(IEnumerableDouble) Evaluates the population variance from the full population provided as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberPopulationVariance(IEnumerableSingle) Evaluates the population variance from the full population provided as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN.
Public methodStatic memberRootMeanSquare(IEnumerableDouble) Estimates the root mean square (RMS) also known as quadratic mean from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberRootMeanSquare(IEnumerableSingle) Estimates the root mean square (RMS) also known as quadratic mean from the enumerable, in a single pass without memoization. Returns NaN if data is empty or any entry is NaN.
Public methodStatic memberStandardDeviation(IEnumerableDouble) Estimates the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public methodStatic memberStandardDeviation(IEnumerableSingle) Estimates the unbiased population standard deviation from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public methodStatic memberVariance(IEnumerableDouble) Estimates the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
Public methodStatic memberVariance(IEnumerableSingle) Estimates the unbiased population variance from the provided samples as enumerable sequence, in a single pass without memoization. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN.
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