BOSO.multiple.warmstart: BOSO.single and associates functions
In BOSO: Bilevel Optimization Selector Operator

Description Usage Arguments Details Value Author(s)

View source: R/BOSO_multiple_WarmStart.R

Function to run a single block BOSO problem, generating one CPLEX object and re-runing it for the different K.

BOSO.multiple.warmstart(
  x,
  y,
  xval,
  yval,
  nlambda = 100,
  IC = "eBIC",
  n.IC = NULL,
  p.IC = NULL,
  lambda.min.ratio = ifelse(nrow(x) < ncol(x), 0.01, 1e-04),
  lambda = NULL,
  intercept = TRUE,
  standardize = FALSE,
  dfmin = 0,
  dfmax = NULL,
  costErrorVal = 1,
  costErrorTrain = 0,
  costVars = 0,
  Threads = 0,
  timeLimit = 1e+75,
  verbose = F,
  TH_IC = 0.001
)

`x`	Input matrix, of dimension 'n' x 'p'. This is the data from the training partition. Its recommended to be class "matrix".
`y`	Response variable for the training dataset. A matrix of one column or a vector, with 'n' elements
`xval`	Input matrix, of dimension 'n' x 'p'. This is the data from the validation partition. Its recommended to be class "matrix".
`yval`	Response variable for the validation dataset. A matrix of one column or a vector, with 'n' elements
`nlambda`	The number of lambda values. Default is 100.
`IC`	information criterion to be used. Default is 'eBIC'.
`n.IC`	number of events for the information criterion.
`p.IC`	number of initial variables for the information criterion.
`lambda.min.ratio`	Smallest value for lambda, as a fraction of lambda.max, the (data derived) entry value
`lambda`	A user supplied lambda sequence. Typical usage is to have the program compute its own lambda sequence based on nlambda and lambda.min.ratio. Supplying a value of lambda overrides this. WARNING: use with care
`intercept`	Boolean variable to indicate if intercept should be added or not. Default is false.
`standardize`	Boolean variable to indicate if data should be scaled according to mean(x) mean(y) and sd(x) or not. Default is false.
`dfmin`	Minimum number of variables to be included in the problem. The intercept is not included in this number. Default is 0.
`dfmax`	Maximum number of variables to be included in the problem. The intercept is not included in this number. Default is min(p,n).
`costErrorVal`	Cost of error of the validation set in the objective function. Default is 1. WARNING: use with care, changing this value changes the formulation presented in the main article.
`costErrorTrain`	Cost of error of the training set in the objective function. Default is 0. WARNING: use with care, changing this value changes the formulation presented in the main article.
`costVars`	Cost of new variables in the objective function. Default is 0. WARNING: use with care, changing this value changes the formulation presented in the main article.
`Threads`	CPLEX parameter, number of cores that cplex is allowed to use. Default is 0 (automatic).
`timeLimit`	CPLEX parameter, time limit per problem provided to CPLEX. Default is 1e75 (infinite time).
`verbose`	print progress. Default is FALSE
`TH_IC`	is the ratio over one that the information criterion must increase to be STOP. Default is 1e-3.