## Usage

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

## Arguments

- object
A `CountMatrix`

object.

- ...
Currently not used.

## Details

Computes for each cell of a numeric matrix one of the following statistic.

## 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
.

## Examples

```
## Abundance data
## Coerce dataset to a count matrix (data from Desachy 2004)
data("compiegne", package = "folio")
counts <- as_count(compiegne)
## Compute EPPM
counts_eppm <- eppm(counts)
## Compute PVI
counts_pvi <- pvi(counts)
plot_heatmap(counts_eppm)
```