VGAM: model.matrixvlm – R documentation

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model.matrixvlm

Construct the Design Matrix of a VLM Object

Description

Creates a design 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.matrixvlm(object, type = c("vlm", "lm", "lm2", "bothlmlm2"),
                linpred.index = NULL, ...)

Arguments

`object`	an object of a class that inherits from the vector linear model (VLM).
`type`	Type of design matrix returned. The first is the default. The value `"vlm"` is the VLM model matrix corresponding to the `formula` argument. The value `"lm"` is the LM model matrix corresponding to the `formula` argument. The value `"lm2"` is the second (LM) model matrix corresponding to the `form2` argument. The value `"bothlmlm2"` means both LM and VLM model matrices.
`linpred.index`	Vector of integers. The index for a linear/additive predictor, it must have values from the set `1:M`. Also, if `length(linpred.index) == 1` then `type = "lm"` must be assigned, whereas if `length(linpred.index) > 1` then `type = "vlm"` must be assigned, Then it returns a subset of the VLM matrix corresponding to the `linpred.index`th linear/additive predictor(s); this is a LM-type matrix when it is of unit length. Currently some attributes are returned, but these may change in value in the future because of ongoing development work.
`...`	further arguments passed to or from other methods. These include `data` (which is a data frame created with `model.framevlm`), `contrasts.arg`, and `xlev`. See `model.matrix` for more information.

Details

This function creates a design matrix from object. This can be a small LM object or a big VLM object (default). The latter is constructed from the former and the constraint matrices.

This code implements smart prediction (see smartpred).

Value

The design matrix for a regression model with the specified formula and data. If type = "bothlmlm2" then a list is returned with components "X" and "Xm2".

Sometimes (especially if x = TRUE when calling vglm) the model matrix has attributes: "assign" ("lm"-type) and "vassign" ("vlm"-type) and "orig.assign.lm" ("lm"-type). These are used internally a lot for bookkeeping, especially regarding the columns of both types of model matrices. In particular, constraint matrices and variable selection relies on this information a lot. The "orig.assign.lm" is the ordinary "assign" attribute for lm and glm objects.

References

Chambers, J. M. (1992). Data for models. Chapter 3 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.

Examples

# (I) Illustrates smart prediction ,,,,,,,,,,,,,,,,,,,,,,,
pneumo <- transform(pneumo, let = log(exposure.time))
fit <- vglm(cbind(normal, mild, severe) ~
            sm.poly(c(sm.scale(let)), 2),
            multinomial, data = pneumo, trace = TRUE, x = FALSE)
class(fit)
fit@smart.prediction  # Data-dependent parameters
fit@x # Not saved on the object
model.matrix(fit)
model.matrix(fit, linpred.index = 1, type = "lm")
model.matrix(fit, linpred.index = 2, type = "lm")

(Check1 <- head(model.matrix(fit, type = "lm")))
(Check2 <- model.matrix(fit, data = head(pneumo), type = "lm"))
all.equal(c(Check1), c(Check2))  # Should be TRUE

q0 <- head(predict(fit))
q1 <- head(predict(fit, newdata = pneumo))
q2 <- predict(fit, newdata = head(pneumo))
all.equal(q0, q1)  # Should be TRUE
all.equal(q1, q2)  # Should be TRUE

# (II) Attributes ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
fit2 <- vglm(cbind(normal, mild, severe) ~ let,  # x = TRUE
             multinomial, data = pneumo, trace = TRUE)
fit2@x  # "lm"-type; saved on the object; note the attributes
model.matrix(fit2, type = "lm")  # Note the attributes
model.matrix(fit2, type = "vlm")  # Note the attributes

VGAM

Vector Generalized Linear and Additive Models

v1.1-5

GPL-3

Authors

Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)

Initial release

2021-01-13