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 transposed 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
.
signature(from = "ddenseModelMatrix", to = "predModule")
:
Creates a "dPredModule"
object.
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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