oscar.control {oscar}

Control OSCAR optimizer parameters

Description

Fine-tuning the parameters available for the DBDC and LMBM optimizers. See oscar documentation for the optimization algorithms for further details.

Usage

oscar.control(
  x,
  family,
  start = 2,
  in_mrounds = 5000,
  in_mit = 5000,
  in_mrounds_esc = 5000,
  in_b1,
  in_b2 = 3,
  in_b,
  in_m = 0.01,
  in_m_clarke = 0.01,
  in_c = 0.1,
  in_r_dec,
  in_r_inc = 10^5,
  in_eps1 = 5 * 10^(-5),
  in_eps,
  in_crit_tol = 10^(-5),
  na = 4,
  mcu = 7,
  mcinit = 7,
  tolf = 10^(-5),
  tolf2 = 10^4,
  tolg = 10^(-5),
  tolg2 = tolg,
  eta = 0.5,
  epsL = 0.125
)

Arguments

x

Input data matrix 'x'; will be used for calculating various control parameter defaults.

family

Model family; should be one of 'cox', 'logistic', or 'gaussian'/'mse'

start

Starting point generation method, see vignettes for details; should be an integer between range,range, Default: 2

in_mrounds

DBDC: The maximum number of rounds in one main iteration, Default: 5000

in_mit

DBDC: The maximum number of main iterations, Default: 5000

in_mrounds_esc

DBDC: The maximum number of rounds in escape procedure, Default: 5000

in_b1

DBDC: The size of bundle B1, Default: min(n_feat+5,1000)

in_b2

DBDC: The size of bundle B2, Default: 3

in_b

DBDC: Bundle B in escape procedure, Default: 2*n_feat

in_m

DBDC: The descent parameter in main iteration, Default: 0.01

in_m_clarke

DBDC: The descent parameter in escape procedure, Default: 0.01

in_c

DBDC: The extra decrease parameter in main iteration, Default: 0.1

in_r_dec

DBDC: The decrease parameter in main iteration, Default: 0.75, 0.99, or larger depending on n_obs (thresholds 10, 300, and above)

in_r_inc

DBDC: The increase parameter in main iteration, Default: 10^5

in_eps1

DBDC: The enlargement parameter, Default: 5*10^(-5)

in_eps

DBDC: The stopping tolerance (proximity measure), Default: 10^(-6) if number of features is <= 50, otherwise 10^(-5)

in_crit_tol

DBDC: The stopping tolerance (criticality tolerance), Default: 10^(-5)

na

LMBM: Size of the bundle, Default: 4

mcu

LMBM: Upper limit for maximum number of stored corrections, Default: 7

mcinit

LMBM: Initial maximum number of stored corrections, Default: 7

tolf

LMBM: Tolerance for change of function values, Default: 10^(-5)

tolf2

LMBM: Second tolerance for change of function values, Default: 10^4

tolg

LMBM: Tolerance for the first termination criterion, Default: 10^(-5)

tolg2

LMBM: Tolerance for the second termination criterion, Default: same as 'tolg'

eta

LMBM: Distance measure parameter (>0), Default: 0.5

epsL

LMBM: Line search parameter (0 < epsL < 0.25), Default: 0.125

Details

This function sanity checks and provides reasonable DBDC ('Double Bundle method for nonsmooth DC optimization' as described in Joki et al. (2018) <doi:10.1137/16M1115733>) and LMBM ('Limited Memory Bundle Method for large-scale nonsmooth optimization' as presented in Haarala et al. (2004) <doi:10.1080/10556780410001689225>) optimization tuning parameters. User may override custom values, though sanity checks will prevent unreasonable values and replace them. The returned list of parameters can be provided for the 'control' parameter when fitting oscar-objects.

Value

A list of sanity checked parameter values for the OSCAR optimizers.

Examples

if(interactive()){
  oscar.control() # Return a list of default parameters
}