BOSO.multiple.coldstart: BOSO.single and associates functions

Description

Function to run a single block BOSO problem, generating for each K a different CPLEX object.

Usage

BOSO.multiple.coldstart(
  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
)

Value

A `BOSO` object.

Arguments

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 IBM ILOG 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.

Author

Luis V. Valcarcel

Details

Compute the BOSO for use one block. This function calls ILOG IBM CPLEX with 'cplexAPI' to solve the optimization problem