bank

The bank dataset we analyze in the first part
of Chapter 3 comes from Flury and Riedwyl (1988) and
is made of four measurements on 100 genuine Swiss banknotes and 100 counterfeit ones.
The response variable \(y\) is thus the status of the banknote, where 0 stands 
for genuine and 1 stands for counterfeit, while the explanatory factors are bill
measurements.

datasets

Allows the reenactment of the R programs used in
the book Bayesian Essentials with R without further programming.
R code being available as well, they can be modified by the user
to conduct one's own simulations.
Marin J.-M. and Robert C. P. (2014) <doi:10.1007/978-1-4614-8687-9>.

JeanMichel Marin

bayess

Bayesian Essentials with R

bank function

A data frame with 200 observations on the following 5 variables.<dl>
 <dt><code>x1</code></dt>
<dd>length of the bill (in mm)</dd> <dt><code>x2</code></dt>
<dd>width of the left edge (in mm)</dd> <dt><code>x3</code></dt>
<dd>width of the right edge (in mm)</dd> <dt><code>x4</code></dt>
<dd>bottom margin width (in mm)</dd> <dt><code>y</code></dt>
<dd>response variable</dd> 
</dl>

Format

bank dataset (Chapter 4) — bank

A data frame with 200 observations on the following 5 variables.<dl>
 <dt><code>x1</code></dt>
<dd>length of the bill (in mm)</dd>

 <dt><code>x2</code></dt>
<dd>width of the left edge (in mm)</dd>

 <dt><code>x3</code></dt>
<dd>width of the right edge (in mm)</dd>

 <dt><code>x4</code></dt>
<dd>bottom margin width (in mm)</dd>

 <dt><code>y</code></dt>
<dd>response variable</dd>

 
</dl>

bank: bank dataset (Chapter 4)

Description

Usage

Arguments

Format

Examples