# mca

##### Multiple Correspondence Analysis

Computes a multiple correspondence analysis of a set of factors.

- Keywords
- multivariate, category

##### Usage

`mca(df, nf = 2, abbrev = FALSE)`

##### Arguments

- df
A data frame containing only factors

- nf
The number of dimensions for the MCA. Rarely 3 might be useful.

- abbrev
Should the vertex names be abbreviated? By default these are of the form ‘factor.level’ but if

`abbrev = TRUE`

they are just ‘level’ which will suffice if the factors have distinct levels.

##### Value

An object of class `"mca"`

, with components

The coordinates of the rows, in `nf`

dimensions.

The coordinates of the column vertices, one for each level of each factor.

Weights for each row, used to interpolate additional factors in `predict.mca`

.

The number of factors

The singular values for the `nf`

dimensions.

The matched call.

##### References

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.* Fourth edition. Springer.

##### See Also

##### Examples

```
# NOT RUN {
farms.mca <- mca(farms, abbrev=TRUE)
farms.mca
plot(farms.mca)
# }
```

*Documentation reproduced from package MASS, version 7.3-51.1, License: GPL-2 | GPL-3*