Independance

## Usage

```
eppm(object, ...)
pvi(object, ...)
# S4 method for CountMatrix
eppm(object)
# S4 method for CountMatrix
pvi(object)
```

## EPPM

This positive difference from the column mean percentage (in french "écart
positif au pourcentage moyen", EPPM) represents a deviation from the
situation of statistical independence. As independence can be interpreted as
the absence of relationships between types and the chronological order of
the assemblages, `EPPM`

is a useful graphical tool to explore significance
of relationship between rows and columns related to seriation (Desachy
2004).

## PVI

`PVI`

is calculated for each cell as the percentage to the column
theoretical independence value: `PVI`

greater than \(1\) represent
positive deviations from the independence, whereas `PVI`

smaller than
\(1\) represent negative deviations (Desachy 2004).

The `PVI`

matrix allows to explore deviations from independence
(an intuitive graphical approach to \(\chi^2\)),
in such a way that a high-contrast matrix has quite significant deviations,
with a low risk of being due to randomness (Desachy 2004).

## References

Desachy, B. (2004). Le sériographe EPPM: un outil informatisé de sériation
graphique pour tableaux de comptages. *Revue archéologique de Picardie*,
3(1), 39-56. doi:10.3406/pica.2004.2396
.

## See also

`plot_ford()`

, `plot_heatmap()`

, `seriate_rank()`

Other statistics:
`test_diversity()`