Kernel Density Class
Contains methods for computing kernel density estimates.
Definition
Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4
C#
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4
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( | Estimates the density of the input |
Estimate( | Estimates the density of the input |
Estimate( | Estimates the density of the input. |
Estimate | Estimates the bandwidth for kernel density estimation using the specified data and method. |
Estimate | Estimates the probability density of the input variable. |
Normal | Returns the bandwidth for kernel density estimation based on Silverman's rule. |
Scott | Returns the bandwidth for kernel density estimation based on Scott's rule. |
Silverman | Returns the bandwidth for kernel density estimation based on Silverman's rule. |
Fields
Biweight | Represents a bi-weight kernel. |
Cosine | Represents a cosine kernel. |
Cosine | Represents an alternative cosine kernel. |
Epanechnikov | Represents an Epanechnikov kernel. |
Gaussian | Represents a Gaussian kernel. |
Logistic | Represents a logistic kernel. |
Triangular | Represents a kernel shaped like a triangle. |
Tricubic | Represents a tri-cubic kernel. |
Triweight | Represents a tri-weight kernel. |
Uniform | Represents a uniform kernel, shaped like a rectangle. |