icm_subset_cpp: Iterative Convex Minorant (ICM) Subset Algorithm
In iclogcondist: Log-Concave Distribution Estimation with Interval-Censored Data

icm_subset_cpp

R Documentation

Iterative Convex Minorant (ICM) Subset Algorithm

Description

This function implements the ICM algorithm for solving the sub-problem in the active set algorithm. This is a support of the active set algorithm, computing the optimal values phi_tilde with reduced number of knots in the sub-problem. It uses backtracking to ensure convergence (Jongbloed, 1998).

Usage

icm_subset_cpp(
  phi_tilde_initial,
  is,
  tau_no_Inf,
  L_Rc,
  Lc_R,
  Lc_Rc,
  ri,
  li,
  weight,
  tol = 1e-10,
  max_iter = 500
)

Arguments

`phi_tilde_initial`	A numeric vector representing the initial values of the reduced variables `phi_tilde`.
`is`	A numeric vector indicating the nodes with unequal left-hand slope and right-hand slope.
`tau_no_Inf`	A numeric vector containing the unique time points, excluding infinity.
`L_Rc`	Indices of observations where the event is in the intersection of L group and the complement of R group. The L group consists of samples with left intervals time <= min(all right intervals time). The R group consists of samples with infinity right interval time.
`Lc_R`	Indices of observations where the event is in the intersection of the complement of L group and R group.
`Lc_Rc`	Indices of observations where the event is in the intersection of the complement of L group and the complement of R group.
`ri`	A numeric vector of indices corresponding to the right bounds of the intervals in `tau_no_Inf`.
`li`	A numeric vector of indices corresponding to the left bounds of the intervals in `tau_no_Inf`.
`weight`	A numeric vector representing the weights for each observation.
`tol`	A numeric value specifying the tolerance for convergence. Default is `1e-10`.
`max_iter`	An integer specifying the maximum number of iterations. Default is `500`.