A nearest-neighbors procedure is used in conjunction with the Epanechnikov kernel to define a kernel smooth of multinomial outcomes across the covariate space
smooth.patterns(dat, kfrac, bw)
The capture-recapture data in the form that is returned by
The approximate fraction of the data that is included in the support of the kernel for the local averages.
A matrix a single column, with rownames that match the covariate
See Kurtz 2013, Chapter on multiple sclerosis
A list containing the original data (
dat), the smoothed data
hpi), and the effective sample sizes (
ess) for each local
average, or row, in the smoothed data
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