surv_dm_solver | R Documentation |
C++
functionThe main optimization function for survival dimensional reduction, the IR-Semi method. This is an internal function and should not be called directly.
surv_dm_solver(
B,
X,
Phit,
Fail_Ind,
bw,
rho,
eta,
gamma,
tau,
epsilon,
btol,
ftol,
gtol,
maxitr,
verbose,
ncore
)
B |
A matrix of the parameters |
X |
The covariate matrix (This matrix is ordered by the order of Y for faster computation) |
Phit |
Phit as defined in Sun et al. (2017) |
Fail_Ind |
The locations of the failure subjects |
bw |
Kernel bandwidth for X |
rho |
(don't change) Parameter for control the linear approximation in line search |
eta |
(don't change) Factor for decreasing the step size in the backtracking line search |
gamma |
(don't change) Parameter for updating C by Zhang and Hager (2004) |
tau |
(don't change) Step size for updating |
epsilon |
(don't change) Parameter for approximating numerical gradient |
btol |
(don't change) The |
ftol |
(don't change) Estimation equation 2-norm tolerance level |
gtol |
(don't change) Gradient tolerance level |
maxitr |
Maximum number of iterations |
verbose |
Should information be displayed |
ncore |
The number of cores for parallel computing |
The optimizer B
for the estimating equation.
Sun, Q., Zhu, R., Wang, T., & Zeng, D. (2019). Counting process-based dimension reduction methods for censored outcomes. Biometrika, 106(1), 181-196. DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/biomet/asy064")}
# This function should be called internally. When having all objects pre-computed, one can call
# surv_solver(B, X, Phit, Fail.Ind,
# rho, eta, gamma, tau, epsilon, btol, ftol, gtol, maxitr, verbose)
# to solve for the parameters B.
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