umontreal.iro.lecuyer.gof
Class KernelDensity
java.lang.Object
umontreal.iro.lecuyer.gof.KernelDensity
public class KernelDensity
- extends Object
This 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 class
KernelDensityGen
in package randvar.
Method Summary |
static double[] |
computeDensity(EmpiricalDist dist,
ContinuousDistribution kern,
double[] Y)
Similar to method ,
but the bandwidth h is obtained from the method
KernelDensityGen.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. |
KernelDensity
public KernelDensity()
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.
computeDensity
public static double[] computeDensity(EmpiricalDist dist,
ContinuousDistribution kern,
double[] Y)
- Similar to method ,
but the bandwidth h is obtained from the method
KernelDensityGen.getBaseBandwidth
(dist) in package randvar.
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