SCOptim: Spherically Constrained Optimization

In SCOR: Spherically Constrained Optimization Routine

Spherically Constrained Optimization

Description

SCOptim runs our optimization algorithm, efficient in estimating maximizing Hyper Volume Under Manifolds Estimators.

Usage

SCOptim(
  x0,
  func,
  rho = 2,
  phi = 0.001,
  max_iter = 50000,
  s_init = 2,
  tol_fun = 1e-06,
  tol_fun_2 = 1e-06,
  minimize = TRUE,
  time = 36000,
  print = FALSE,
  lambda = 0.001,
  parallel = FALSE
)

Arguments

x0	The initial guess by user
func	The function to be optimized
rho	Step Decay Rate with default value 2
phi	Lower Bound Of Global Step Size. Default value is 10^{-6}
max_iter	Max Number Of Iterations In each Run. Default Value is 50,000.
s_init	Initial Global Step Size. Default Value is 2.
tol_fun	Termination Tolerance on the function value. Default Value is 10^{-6}
tol_fun_2	Termination Tolerance on the difference of solutions in two consecutive runs. Default Value is 10^{-6}
minimize	Binary Command to set SCOptim on minimization or maximization. TRUE is for minimization which is set default.
time	Time Allotted for execution of SCOptim
print	Binary Command to print optimized value of objective function after each iteration. FALSE is set fault
lambda	Sparsity Threshold. Default value is 10^{-3}
parallel	Binary Command to ask SCOptim to perform parallel computing. Default is set at FALSE.

Details

SCOptim is the modified version of RMPS, Recursive Modified Pattern Search. This is a blackbox algorithm efficient in optimizing non-differentiable functions. It works great in the shown cases of SHUM, EHUM and ULBA.

Value

The point where the value Of the Function is maximized under a sphere.

References

• Das, Priyam and De, Debsurya and Maiti, Raju and Chakraborty, Bibhas and Peterson, Christine B
  "Estimating the Optimal Linear Combination of Biomarkers using Spherically Constrained Optimization"
  (available at 'arXiv https://arxiv.org/abs/1909.04024).

Examples

f <- function(x)
return(x[2]^2 + x[3]^3 +x[4]^4)

SCOptim(rep(1,10), f)

SCOptim(c(2,4,6,2,1), f, minimize = FALSE, print = TRUE)
#Will Print the List and Find the Maximum

SCOptim(c(1,2,3,4), f, time = 10, lambda = 1e-2)
#Will perform no iterations after 10 secs, Sparsity Threshold is 0.01

SCOR documentation built on July 9, 2023, 6:39 p.m.