MRSP.list-class: Class '"MRSP.list"'
In MRSP: Multinomial Response Models with Structured Penalties

Description Objects from the Class Methods Author(s) References See Also Examples

An object containing the output of MRSP-calls with more than one tuning parameter value, i.e. model output related to a whole “coefficient path”. With nrlambda denoting the number of different lambda values for which to fit a penalized multinomial response model, MRSP.list-objects are lists of length nrlambda. Each entry of this list is an object of class MRSP and contains the model output for one concrete lambda value. If an MRSP.list-object was created by function MRSP, it additionally has attributes “topcall”, “call” and “dat”. Those attributes store, respectively, the call to MRSP, the call to MRSP.fit which was prepared by MRSP and the data object to be supplied to MRSP.fit. Note that dat contains the standardized covariates if standardize = TRUE.

Objects of this class are created by function MRSP.fit, which will most likely be called internally by the end-user function MRSP.

cv: signature(object = "MRSP.list"): cv(object, k, type, parallel, cores, ...) performs k-fold crossvalidation of the models in object. The output is a list whose entry mean gives the mean values of the criterion specified via argument type over the crossvalidation folds; for each model found in object. type can be "deviance" (the default), "loglik" or "brier", using the deviance, loglikelihood or the Brier score. Depending on the logical argument parallel and integer argument cores, crossvalidation is performed either serially or with cores parallel processes.
extract: signature(object = "MRSP.list"): extract(object, slotname) returns the value of the slot whose name was given as a character string from all elements of object. The result is coerced to a vector or matrix if appropriate.
getCall: signature(x = "MRSP.list"): Get the call that created the MRSP.list-object.
plot: signature(x = "MRSP.list"): Plot coefficient paths.

select: signature(object = "MRSP.list"): select(object, criterion=c("AIC","BIC","cv"), ...) selects one concrete MRSP model from object based on criterion. For criterion="cv", an additional, integer argument k, a logical argument parallel and an integer argument cores can be supplied, see cv above.

show: signature(object = "MRSP.list"): Print some basic infos about the MRSP.list object.

Wolfgang Poessnecker

Tutz, G., Poessnecker, W., Uhlmann, L. (2015) Variable Selection in General Multinomial Logit Models
Computational Statistics and Data Analysis, Vol. 82, 207-222.
http://www.sciencedirect.com/science/article/pii/S0167947314002709

MRSP