ferg.df | R Documentation |
Function to compute an approximation of Ferguson's estimator mu_n.
ferg.df(x, alpha, mu, npoints,...)
x |
a vector of data of length n |
alpha |
the degree of confidence in mu |
mu |
the prior guess of the unknown P (a pdf) |
npoints |
the number of estimated points returned |
... |
all of the arguments needed for mu |
The function returns a vector of length num.points for Ferguson's estimator.
Rachel Becvarik
See Section 16.2 of Hollander, Wolfe, Chicken - Nonparametric Statistical Methods 3.
##Hollander-Wolfe-Chicken Figure 16.2
framingham<-c(2273, 2710, 141, 4725, 5010, 6224, 4991, 458, 1587, 1435, 2565, 1863)
plot.ecdf(framingham)
lines(sort(framingham),pexp(sort(framingham), 1/2922), lty=3)
temp.x = seq(min(framingham), max(framingham), length.out=100)
lines(temp.x,ferg.df(sort(framingham), 4, npoints=100,pexp,1/2922), col=2, type="s", lty=2)
legend("bottomright", lty=c(1,3,2), legend=c("ecdf", "prior", "ferguson"), col=c(1,1,2))
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