mklewarp {MKLE} | R Documentation |
Computes the maximum kernel likelihood estimator for a given dataset and bandwidth using fast fourier transforms.
mklewarp(data, bw = 1, gs = 2^11, K="gaussian")
data |
the data for which the log likelihood will be computed. |
bw |
the smoothing bandwidth to be used. |
gs |
the number of gridpoints to be used for the fourier transform |
K |
a character string giving the kernel function to be used. This must be one of '"gaussian"', '"rectangular"', '"triangular"', '"epanechnikov"', '"biweight"', '"cosine"' or '"optcosine"', with default '"gaussian"'. |
The underlying shifted kernel density estimator is defined as
frac{1}{nh}sum_{i=1}^nK(frac{y-X_i-bar X+theta}{h})
. The default for the bandwidth is 2*sigma, which is the optimal value if a Gaussian kernel is used.
the MKLE.
Thomas Jaki
~coming soon ~
## compares the MKLE and the warped MKLE. data(state) attach(state) mkle(crime) mklewarp(crime)