# ferg.df: Ferguson's Estimator In NSM3: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition

## Description

Function to compute an approximation of Ferguson's estimator mu_n.

## Usage

 `1` ```ferg.df(x, alpha, mu, npoints,...) ```

## Arguments

 `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

## Value

The function returns a vector of length num.points for Ferguson's estimator.

Rachel Becvarik

## References

See Section 16.2 of Hollander, Wolfe, Chicken - Nonparametric Statistical Methods 3.

## Examples

 ```1 2 3 4 5 6 7``` ```##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)) ```

NSM3 documentation built on April 6, 2021, 5:05 p.m.