BOSO.single {BOSO}

BOSO.single and associates functions

Description

Bonjour

Usage

BOSO.single(
  x,
  y,
  xval,
  yval,
  nlambda = 100,
  lambda.min.ratio = ifelse(nrow(x) < ncol(x), 0.01, 1e-04),
  lambda = NULL,
  intercept = TRUE,
  standardize = TRUE,
  dfmin = 0,
  dfmax = NULL,
  costErrorVal = 1,
  costErrorTrain = 0,
  costVars = 0,
  Threads = 0,
  timeLimit = 1e+75
)

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.

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).

Details

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

Author(s)

Luis V. Valcarcel