R: Construct the Model Matrix of a QRR-VGLM Object

model.matrixqrrvglm {VGAM} | R Documentation

## Construct the Model Matrix of a QRR-VGLM Object

### Description

Creates a model matrix. Two types can be returned: a large one (class `"vlm"` or one that inherits from this such as `"vglm"`) or a small one (such as returned if it were of class `"lm"`).

### Usage

    model.matrixqrrvglm(object, type = c("latvar", "lm", "vlm"), ...)

### Arguments

`object` | an object of a class `"qrrvglm"`, i.e., a `cqo` object.
`type` | Type of model (or design) matrix returned. The first is the default. The value `"latvar"` is model matrix mainly comprising of the latent variable values (sometimes called the site scores). The value `"lm"` is the LM matrix directly corresponding to the `formula` argument. The value `"vlm"` is the big VLM model matrix given C.
`...` | further arguments passed to or from other methods.

### Details

This function creates one of several design matrices from `object`. For example, this can be a small LM object or a big VLM object.

When `type = "vlm"` this function calls `fnumat2R()` to construct the big model matrix given C. That is, the constrained coefficients are assumed known, so that something like a large Poisson or logistic regression is set up. This is because all responses are fitted simultaneously here. The columns are labelled in the following order and with the following prefixes: `"A"` for the A matrix (linear in the latent variables), `"D"` for the D matrix (quadratic in the latent variables), `"x1."` for the B_1 matrix (usually contains the intercept; see the argument `noRRR` in `qrrvglm.control`).

### Value

The design matrix after scaling for a regression model with the specified formula and data. By after scaling, it is meant that it matches the output of `coef(qrrvglmObject)` rather than the original scaling of the fitted object.

### See Also

`model.matrixvlm`, `cqo`, `vcovqrrvglm`.

### Examples

    ## Not run:
    set.seed(1); n <- 40; p <- 3; S <- 4; myrank <- 1
    mydata <- rcqo(n, p, S, Rank = myrank, es.opt = TRUE, eq.max = TRUE)
    (myform <- attr(mydata, "formula"))
    mycqo <- cqo(myform, poissonff, data = mydata,
                 I.tol = TRUE, Rank = myrank, Bestof = 5)
    model.matrix(mycqo, type = "latvar")
    model.matrix(mycqo, type = "lm")
    model.matrix(mycqo, type = "vlm")

    ## End(Not run)

[Package VGAM version 1.1-3 Index]