predModule-class | R Documentation |

The class `"predModule"`

and notably its subclasses
`"dPredModule"`

and `"sPredModule"`

encapsulate information
about linear predictors in statistical models. They incorporate a
`modelMatrix`

, the corresponding coefficients and a
representation of a triangular factor from the, possibly weighted or
otherwise modified, model matrix.

Objects are typically created by coercion from objects of class
`ddenseModelMatrix`

or
`dsparseModelMatrix`

.

The virtual class `"predModule"`

and its two subclasses all have slots

`X`

:a

`modelMatrix`

.`coef`

:`"numeric"`

coefficient vector of length`ncol(.)`

`:= p`

.`Vtr`

:`"numeric"`

vector of length`p`

, to contain`V'r`

(“**V****t**ransposed**r**”).`fac`

:a representation of a triangular factor, the Cholesky decomposition of

`V'V`

.

The actual classes `"dPredModule"`

and `"sPredModule"`

specify specific (sub) classes for the two non-trivial slots,

`X`

:a

`"ddenseModelMatrix"`

or`"dsparseModelMatrix"`

, respectively.`fac`

:For the

`"dpredModule"`

class this factor is a`Cholesky`

object. For the`"spredModule"`

class it is of class`CHMfactor`

.

- coerce
`signature(from = "ddenseModelMatrix", to = "predModule")`

: Creates a`"dPredModule"`

object.- coerce
`signature(from = "dsparseModelMatrix", to = "predModule")`

: Creates an`"sPredModule"`

object.

Douglas Bates

`model.Matrix()`

which returns a
`"ddenseModelMatrix"`

or
`"dsparseModelMatrix"`

object, depending if its
`sparse`

argument is false or true. In both cases, the resulting
`"modelMatrix"`

can then be coerced to a sparse or dense
`"predModule"`

.

```
showClass("dPredModule")
showClass("sPredModule")
## see example(model.Matrix)
```

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