RunningStatistics 0.3.1

RunningStatistics

Online (single pass) algorithms for statistical measures based on the Julia package OnlineStats.jl by Josh Day. Useful for streaming and big data.

List of Statistics

Methods

The IRunningStatistic<in TObs> interface provides the following members:

public interface IRunningStatistic<in TObs>
{
    public long Nobs { get; }

    public void Fit(IEnumerable<TObs> values);

    public void Fit(TObs value);

    public void Reset();
}

The IRunningStatistic<in TObs, out TValue> interface provides the additional member:

public interface IRunningStatistic<in TObs, out TValue> : IRunningStatistic<TObs>
{
    public TValue Value { get; }
}

Finally each statistic implements IRunningStatistic<in TObs, out TValue, TSelf> to ensure a consistent set of functionality:

public interface IRunningStatistic<in TObs, out TValue, TSelf> : IRunningStatistic<TObs, TValue> where TSelf : IRunningStatistic<TObs, TValue, TSelf>
{
    public TSelf CloneEmpty();

    public TSelf Clone();

    public void Merge(TSelf other);

    public static abstract TSelf Merge(TSelf first, TSelf second);
}

Therefore merging can only be done when the concrete classes are known, and concrete classes may be cloned.

Examples

using RunningStatistics;

var mean1 = new Mean();
var mean2 = new Mean();
var ecdf = new EmpiricalCdf();

var rng = new Random();
for (var i = 0; i < 1000; i++)
{
    var x = rng.NextDouble();
    
    mean1.Fit(x);
    mean2.Fit(2*x);
    
    ecdf.Fit(x);
}

mean1.Merge(mean2);
var q1 = ecdf.Quantile(0.25);