Namespaces

Types in MathNet.Numerics.Statistics

Type RunningStatistics

Namespace MathNet.Numerics.Statistics

Running statistics accumulator, allows updating by adding values or by combining two accumulators.
This type declares a DataContract for out of the box ephemeral serialization with engines like DataContractSerializer, Protocol Buffers and FsPickler, but does not guarantee any compatibility between versions. It is not recommended to rely on this mechanism for durable persistance.

Constructors

Static Functions

Methods

Properties

Public Constructors

RunningStatistics()

RunningStatistics(IEnumerable<double> values)

Public Static Functions

RunningStatistics Combine(RunningStatistics a, RunningStatistics b)

Create a new running statistics over the combined samples of two existing running statistics.

Public Methods

bool Equals(object obj)

int GetHashCode()

Type GetType()

void Push(double value)

Update the running statistics by adding another observed sample (in-place).

void PushRange(IEnumerable<double> values)

Update the running statistics by adding a sequence of observed sample (in-place).

string ToString()

Public Properties

long Count get;

Gets the total number of samples.

double Kurtosis get;

Estimates the unbiased population kurtosis from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than four entries or if any entry is NaN.

double Maximum get;

Returns the maximum value in the sample data. Returns NaN if data is empty or if any entry is NaN.

double Mean get;

Evaluates the sample mean, an estimate of the population mean. Returns NaN if data is empty or if any entry is NaN.

double Minimum get;

Returns the minimum value in the sample data. Returns NaN if data is empty or if any entry is NaN.

double PopulationKurtosis get;

Evaluates the population kurtosis from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than three entries or if any entry is NaN.

double PopulationSkewness get;

Evaluates the population skewness from the full population. Does not use a normalizer and would thus be biased if applied to a subset (type 1). Returns NaN if data has less than two entries or if any entry is NaN.

double PopulationStandardDeviation get;

Evaluates the standard deviation from the provided full population. 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.

double PopulationVariance get;

Evaluates the variance from the provided full population. 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.

double Skewness get;

Estimates the unbiased population skewness from the provided samples. Uses a normalizer (Bessel's correction; type 2). Returns NaN if data has less than three entries or if any entry is NaN.

double StandardDeviation get;

Estimates the unbiased population standard deviation from the provided samples. 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.

double Variance get;

Estimates the unbiased population variance from the provided samples. 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.