Contains methods for computing kernel density estimates.
SystemObject Extreme.StatisticsKernelDensity
Namespace:
Extreme.Statistics
Assembly:
Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
public static class KernelDensity
Public NotInheritable Class KernelDensity
public ref class KernelDensity abstract sealed
[<AbstractClassAttribute>]
[<SealedAttribute>]
type KernelDensity = class end
The KernelDensity type exposes the following members.
|
| Name | Description |
|---|
  | Estimate(VectorDouble, Kernel, VectorDouble, Double, KernelDensityBandwidthEstimator, Double) |
Estimates the density of the input
|
| Estimate(VectorDouble, Kernel, Double, Double, KernelDensityBandwidthEstimator, Double) |
Estimates the density of the input
|
| Estimate(VectorDouble, 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.
|
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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.
Reference