KernelDensity Class

Contains methods for computing kernel density estimates.

Definition

Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.3
C# 
public static class KernelDensity
Inheritance
Object  →  KernelDensity

Remarks

Use the methods in the KernelDensity class to perform kernel density estimation on a variable. Methods for estimating a suitable bandwidth are also available.

KernelDensity also defines several kernels, including the GaussianKernel, UniformKernel (flat top kernel), and EpanechnikovKernel.

Methods

Estimate(Vector<Double>, Kernel, Vector<Double>, Double, KernelDensityBandwidthEstimator, Double) Estimates the density of the input
Estimate(Vector<Double>, Kernel, Double, Double, KernelDensityBandwidthEstimator, Double) Estimates the density of the input
Estimate(Vector<Double>, Kernel, Int32, Double, Double, Double, Double, KernelDensityBandwidthEstimator, Double) Estimates the density of the input.
EstimateBandwidth Estimates the bandwidth for kernel density estimation using the specified data and method.
EstimateDistribution Estimates the probability density of the input variable.
NormalReferenceBandwidth Returns the bandwidth for kernel density estimation based on Silverman's rule.
ScottBandwidth Returns the bandwidth for kernel density estimation based on Scott's rule.
SilvermanBandwidth Returns the bandwidth for kernel density estimation based on Silverman's rule.

Fields

BiweightKernel Represents a bi-weight kernel.
CosineKernel Represents a cosine kernel.
CosineKernel2 Represents an alternative cosine kernel.
EpanechnikovKernel Represents an Epanechnikov kernel.
GaussianKernel Represents a Gaussian kernel.
LogisticKernel Represents a logistic kernel.
TriangularKernel Represents a kernel shaped like a triangle.
TricubicKernel Represents a tri-cubic kernel.
TriweightKernel Represents a tri-weight kernel.
UniformKernel Represents a uniform kernel, shaped like a rectangle.

See Also