umontreal.iro.lecuyer.gof
Class KernelDensity
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- umontreal.iro.lecuyer.gof.KernelDensity
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public class KernelDensity extends java.lang.ObjectThis class provides methods to compute a kernel density estimator from a set of n individual observations x0,…, xn-1, and returns its value at m selected points. For details on how the kernel density is defined, and how to select the kernel and the bandwidth h, see the documentation of classKernelDensityGenin package randvar.
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Constructor Summary
Constructors Constructor and Description KernelDensity()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method and Description static double[]computeDensity(EmpiricalDist dist, ContinuousDistribution kern, double[] Y)Similar to method , but the bandwidth h is obtained from the methodKernelDensityGen.getBaseBandwidth(dist) in package randvar.static double[]computeDensity(EmpiricalDist dist, ContinuousDistribution kern, double h, double[] Y)Given the empirical distribution dist, this method computes the kernel density estimate at each of the m points Y[j], j = 0, 1,…,(m - 1), where m is the length of Y, the kernel is kern.density(x), and the bandwidth is h.
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Method Detail
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computeDensity
public static double[] computeDensity(EmpiricalDist dist, ContinuousDistribution kern, double h, double[] Y)
Given the empirical distribution dist, this method computes the kernel density estimate at each of the m points Y[j], j = 0, 1,…,(m - 1), where m is the length of Y, the kernel is kern.density(x), and the bandwidth is h. Returns the estimates as an array of m values.
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computeDensity
public static double[] computeDensity(EmpiricalDist dist, ContinuousDistribution kern, double[] Y)
Similar to method , but the bandwidth h is obtained from the methodKernelDensityGen.getBaseBandwidth(dist) in package randvar.
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