titanDat

<p>Relationship between survival and passenger class on the Titanic. The records of the sinking of the Titanic were studied to establish the relationship between survival and passenger class on the ship. For each person on board the ocean liner, this dataset records sex, age (child/adult), class (crew, 1st, 2nd, 3rd class) and whether or not the person survived.</p>

datasets

Implements a Markov Chain Monte Carlo algorithm to approximate
exact conditional inference for logistic regression models. Exact
conditional inference is based on the distribution of the sufficient
statistics for the parameters of interest given the sufficient statistics
for the remaining nuisance parameters. Using model formula notation, users
specify a logistic model and model terms of interest for exact inference.
See Zamar et al. (2007) <doi:10.18637/jss.v021.i03> for more details.

David Zamar

elrm

Exact Logistic Regression via MCMC

Jinko Graham

Brad McNeney

titanDat function

<p>Matrix with columns:</p><table><tr><td>
[,1] </td>
<td> surv </td>
<td> numeric </td>
<td> number of survivors </td>
</tr><tr><td>
[,2] </td>
<td> n </td>
<td> numeric </td>
<td>  total number of people </td>
</tr><tr><td>
[,3] </td>
<td> class </td>
<td> numeric </td>
<td> passenger class (0 = crew, 1 = first, 2 = second, 3 = third) </td>
</tr><tr><td>
[,4] </td>
<td> age </td>
<td> numeric </td>
<td> age group (1 = adult, 0 = child)) </td>
</tr><tr><td>
[,5] </td>
<td> sex </td>
<td> numeric </td>
<td> gender (1 = male, 0 = female) </td>
</tr></table>

titanDat: Titanic Dataset

Description

Usage

Arguments

Format

References

[,1]	surv	numeric	number of survivors
[,2]	n	numeric	total number of people
[,3]	class	numeric	passenger class (0 = crew, 1 = first, 2 = second, 3 = third)
[,4]	age	numeric	age group (1 = adult, 0 = child))
[,5]	sex	numeric	gender (1 = male, 0 = female)