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StreamingStatistics Methods

The StreamingStatistics type exposes the following members.

Methods
  NameDescription
Public methodStatic memberCovariance
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 memberMaximum
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 memberMean
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
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
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
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 memberPopulationCovariance
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
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
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
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
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
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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