Description Slots Methods See Also

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*lambda1*.`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*l1*or*l-infinity*) for which the model has eventually been fitted.`lambda2`

:Scalar (class

`"numeric"`

) for the amount of*l2*(ridge-like) penalty.`struct`

:Object of class

`"Matrix"`

used to structure the coefficients in the*l2*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`

.

jchiquet/quadrupenCRAN documentation built on May 1, 2018, 12:26 a.m.

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