R: Construct Design Matrices

model.matrixBayes {arm} | R Documentation

## Construct Design Matrices

### Description

`model.matrixBayes` creates a design matrix.

### Usage

    model.matrixBayes(object, data = environment(object),
        contrasts.arg = NULL, xlev = NULL, keep.order = FALSE, drop.baseline=FALSE,...)

### Arguments

`object` | an object of an appropriate class. For the default method, a model formula or terms object.
`data` | a data frame created with `model.frame`. If another sort of object, `model.frame` is called first.
`contrasts.arg` | A list, whose entries are contrasts suitable for input to the `contrasts` replacement function and whose names are the names of columns of `data` containing `factor`s.
`xlev` | to be used as argument of `model.frame` if `data` has no `"terms"` attribute.
`keep.order` | a logical value indicating whether the terms should keep their positions. If `FALSE` the terms are reordered so that main effects come first, followed by the interactions, all second-order, all third-order and so on. Effects of a given order are kept in the order specified.
`drop.baseline` | Drop the base level of categorical Xs, default is TRUE.

`...` | further arguments passed to or from other methods.

### Details

`model.matrixBayes` is adapted from `model.matrix` in the `stats` pacakge and is designed for the use of `bayesglm`. It is designed to keep baseline levels of all categorical varaibles and keep the variable names unodered in the output. The design matrices created by `model.matrixBayes` are unidentifiable using classical regression methods, though; they can be identified using `bayesglm`.

### Author(s)

Yu-Sung Su suyusung@tsinghua.edu.cn

### References

Andrew Gelman, Aleks Jakulin, Maria Grazia Pittau and Yu-Sung Su. (2009). “A Weakly Informative Default Prior Distribution For Logistic And Other Regression Models.” The Annals of Applied Statistics 2 (4): 1360–1383. http://www.stat.columbia.edu/~gelman/research/published/priors11.pdf

### See Also

`model.frame`, `model.extract`, `terms`, `terms.formula`, `bayesglm`.

### Examples

    ff <- log(Volume) ~ log(Height) + log(Girth)
    str(m <- model.frame(ff, trees))
    (model.matrix(ff, m))
    class(ff) <- c("bayesglm", "terms", "formula")
    (model.matrixBayes(ff, m))

[Package arm version 1.9-3 Index]