# bs: Simulated Sample from Binomial Distribution In ACSWR: A Companion Package for the Book "A Course in Statistics with R"

## Description

The data set is used to understand the sampling variation of the score function. The simulated data is available in Pawitan (2001).

## Usage

 `1` ```data(bs) ```

## Format

A data frame with 10 observations on the following 20 variables.

`Sample.1`

a numeric vector

`Sample.2`

a numeric vector

`Sample.3`

a numeric vector

`Sample.4`

a numeric vector

`Sample.5`

a numeric vector

`Sample.6`

a numeric vector

`Sample.7`

a numeric vector

`Sample.8`

a numeric vector

`Sample.9`

a numeric vector

`Sample.10`

a numeric vector

`Sample.11`

a numeric vector

`Sample.12`

a numeric vector

`Sample.13`

a numeric vector

`Sample.14`

a numeric vector

`Sample.15`

a numeric vector

`Sample.16`

a numeric vector

`Sample.17`

a numeric vector

`Sample.18`

a numeric vector

`Sample.19`

a numeric vector

`Sample.20`

a numeric vector

## Source

Pawitan, Y. (2001). In All Likelihood. Oxford Science Publications.

## References

Pawitan, Y. (2001). In All Likelihood. Oxford Science Publications.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```data(bs) n <- 10 sample_means <- colMeans(bs) binomial_score_fn <- function(p,xbar) n*(xbar-10*p)/(p*(1-p)) p <- seq(from=0,to=1,by=0.02) plot(p,sapply(p,binomial_score_fn,xbar=sample_means[1]),"l",xlab=expression(p), ylab=expression(S(p))) title(main="C: Score Function Plot of Binomial Model") for(i in 2:20) lines(p,sapply(p, binomial_score_fn,xbar=sample_means[i]),"l") abline(v=4) abline(h=0) ```

ACSWR documentation built on May 2, 2019, 6:53 a.m.