riskscores (version 1.2.3)

risk_mod_random_start: Run risk model with random start

Description

Runs nstart iterations of risk_mod(), each with a different warm start, and selects the best model. Each coefficient start is randomly selected as -1, 0, or 1.

Usage

risk_mod_random_start(
  X,
  y,
  weights = NULL,
  lambda0 = 0,
  a = -10,
  b = 10,
  max_iters = 100,
  tol = 1e-05,
  seed = NULL,
  nstart = 5
)

Arguments

X

Input covariate matrix with dimension \(n \times p\); every row is an observation.

y

Numeric vector for the (binomial) response variable.

weights

Numeric vector of length \(n\) with weights for each observation. Unless otherwise specified, default will give equal weight to each observation.

lambda0

Penalty coefficient for L0 term (default: 0). See cv_risk_mod() for lambda0 tuning.

a

Integer lower bound for coefficients (default: -10).

b

Integer upper bound for coefficients (default: 10).

max_iters

Maximum number of iterations (default: 10000).

tol

Tolerance for convergence (default: 1e-5).

seed

An integer that is used as argument by set.seed() for offsetting the random number generator. Default is to not set a particular randomization seed.

nstart

Number of different random starts to try (default: 5).