parzen {modeest}R Documentation

Parzen's Kernel Mode Estimator

Description

Parzen's kernel mode estimator is the value maximizing the kernel density estimate.

Usage

parzen(x, 
       bw = NULL, 
       kernel = "gaussian", 
       biau = FALSE, 
       par = shorth(x), 
       optim.method = "BFGS", 
       ...)

Arguments

x numeric. Vector of observations.
bw numeric. The smoothing bandwidth to be used.
kernel character. The kernel to be used. Available kernels are "biweight", "cosine", "eddy", "epanechnikov", "gaussian", "optcosine", "rectangular", "triangular", "uniform". See density.default for more details on some of these kernels.
biau logical. If FALSE (the default), the kernel density estimate is maximised using optim.
par numeric. The initial value used in optim.
optim.method character. If biau = FALSE, the method used in optim.
... if biau = FALSE, further arguments to be passed to optim, or further arguments to be passed to plot.default.

Details

If kernel = "uniform", the naive mode estimate is returned.

Value

parzen returns a numeric value, the mode estimate. If biau = TRUE, the x value maximizing the density estimate is returned. Otherwise, the optim method is used to perform maximization, and the attributes: 'value', 'counts', 'convergence' and 'message', coming from the optim method, are added to the result.

Note

The user should preferentially call parzen through mlv(x, method = "kernel", ...) or mlv(x, method = "parzen", ...). This returns an object of class mlv.

Presently, mlv.kernel is quite slow.

Author(s)

Paul Poncet paulponcet@yahoo.fr

References

See Also

mlv, naive

Examples

# Unimodal distribution
x <- rlnorm(10000, meanlog = 3.4, sdlog = 0.2)
## True mode
lnormMode(meanlog = 3.4, sdlog = 0.2)
## Estimate of the mode
M <- mlv(x, method = "kernel", kernel = "gaussian", bw = 0.3, par = shorth(x))
print(M)
plot(M)

[Package modeest version 1.06 Index]