quadrupen-class | R Documentation |
Class of object returned by any fitting function of the
quadrupen package (elastic.net
or
bounded.reg
).
coefficients
:Matrix (class "dgCMatrix"
) of
coefficients with respect to the original input. The number of
rows corresponds the length of lambda1
.
active.set
:Matrix (class "dgCMatrix"
, generally
sparse) indicating the 'active' variables, in the sense that they
activate the constraints. For the elastic.net
, it
corresponds to the nonzero variables; for the
bounded.reg
function, it is the set of variables
reaching the boundary along the path of solutions.
intercept
:logical; indicates if an intercept has been included to the model.
mu
:A vector (class "numeric"
)
containing the successive values of the (unpenalized) intercept.
Equals to zero if intercept
has been set to FALSE
.
meanx
:Vector (class "numeric"
) containing
the column means of the predictor matrix.
normx
:Vector (class "numeric"
) containing the
square root of the sum of squares of each column of the design
matrix.
penscale
:Vector "numeric"
with real positive
values that have been used to weight the penalty tuned by
\lambda_1
.
penalty
:Object of class "character"
indicating the method used ("elastic-net"
or "bounded
regression"
).
naive
:logical; was the naive
mode on?
lambda1
:Vector (class "numeric"
) of penalty
levels (either \ell_1
or \ell_\infty
)
for which the model has eventually been fitted.
lambda2
:Scalar (class "numeric"
) for the
amount of \ell_2
(ridge-like) penalty.
struct
:Object of class "Matrix"
used to
structure the coefficients in the \ell_2
penalty.
control
:Object of class "list"
with low
level options used for optimization.
monitoring
:List (class "list"
) which
contains various indicators dealing with the optimization
process.
residuals
:Matrix of residuals, each column
corresponding to a value of lambda1
.
r.squared
:Vector (class "numeric"
) given the
coefficient of determination as a function of lambda1.
fitted
:Matrix of fitted values, each column
corresponding to a value of lambda1
.
This class comes with the usual predict(object, newx, ...)
,
fitted(object, ...)
, residuals(object, ...)
,
print(object, ...)
, show(object)
and
deviance(object, ...)
generic (undocumented) methods.
A specific plotting method is available and documented
(plot,quadrupen-method
).
See also plot,quadrupen-method
.
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