regFit function

survivalsvm (regression approach)

The function regFit fits a survivalsvm model based on the regression approach.

regFit(
  X,
  Y,
  delta,
  meth_par = 1,
  kernel_type = "lin_kernel",
  kernel_pars = NA,
  bin_cat = integer(0),
  opt_alg = "quadprog",
  sgf_sv = 5,
  sigf = 7,
  maxiter = 20,
  margin = 0.05,
  bound = 10,
  eig.tol = 1e-06,
  conv.tol = 1e-07,
  posd.tol = 1e-08
)

Arguments

• X: [matrix(1)]

  design matrix.

• Y: [vector(1)]

  vector of survival times.

• delta: [vector(1)]

  vector of status: 0 if censored and 1 else.

• meth_par: [numeric(1)]

  parameter of regularization.

• kernel_type: [character(1)]

  type of the kernel.

• kernel_pars: [vector(1)]

  parameter of kernel.

• bin_cat: [vector(1)]

  indexes of binary/categorial variables.

• opt_alg: [character(1)]

  program used to solve the optimization problem. This most be one of the two possibilities quadprog or ipop.

• sgf_sv: [integer(1)]

  number of digits to be retained in the solution.

• sigf: [integer(1)]

  used by ipop. See ipop for more details.

• maxiter: [integer(1)]

  used by ipop. See ipop for more details.

• margin: [numeric(1)]

  used by ipop. See ipop for more details.

• bound: [numeric(1)]

  used by ipop. See ipop for more details.

• eig.tol: [numeric(1)]

  used by nearPD for adjusting positive definiteness. See nearPD for detail.

• conv.tol: [numeric(1)]

  used by nearPD for adjusting positive definiteness. See nearPD for detail.

• posd.tol: [numeric(1)]

  used by nearPD for adjusting positive definiteness. See nearPD for detail.

Returns

[RegFitObj(1)] object of class RegFitObj containing elements:

Beta	solution of the quadratic optimization problem,
SV	support vector machines,
Kernel	kernel matrix, an object of class Kernel ,
b0	estimated offset,
OptMeth	program used to solve the quadratic optimization problem.

Author(s)

Cesaire J. K. Fouodo