 | 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 HierarchyNamespace: MathNet.Numerics.Statistics
Assembly: MathNet.Numerics (in MathNet.Numerics.dll) Version: 3.7
SyntaxC#
public static class StreamingStatistics
The StreamingStatistics type exposes the following members.
Methods| Name | Description | |
|---|---|---|
  | Covariance |
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.
|
| Entropy |
Calculates the entropy of a stream of double values.
Returns NaN if any of the values in the stream are NaN.
|
| Maximum |
Returns the largest value from the enumerable, in a single pass without memoization.
Returns NaN if data is empty or any entry is NaN.
|
| Mean |
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.
|
| MeanStandardDeviation |
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.
|
| MeanVariance |
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.
|
| Minimum |
Returns the smallest value from the enumerable, in a single pass without memoization.
Returns NaN if data is empty or any entry is NaN.
|
| PopulationCovariance |
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.
|
| PopulationStandardDeviation |
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.
|
| PopulationVariance |
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.
|
| RootMeanSquare |
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.
|
| StandardDeviation |
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.
|
| Variance |
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.
|
See AlsoReference
MathNet.Numerics.StatisticsStreamingStatistics