cpp_COX_gaga: Fit a Cox model via the GAGA algorithm using cpp.

In GAGAs: Global Adaptive Generative Adjustment Algorithm for Generalized Linear Models

Fit a Cox model via the GAGA algorithm using cpp.

Description

Fit a Cox model via the Global Adaptive Generative Adjustment algorithm. Part of this function refers to the coxphfit function in MATLAB 2016b.

Usage

cpp_COX_gaga(
  X,
  y,
  cens,
  alpha = 2,
  itrNum = 50L,
  thresh = 0.001,
  flag = TRUE,
  lamda_0 = 0.5,
  fdiag = TRUE,
  subItrNum = 20L
)

Arguments

X	Input matrix, of dimension nobs*nvars; each row is an observation. If the intercept term needs to be considered in the estimation process, then the first column of X must be all 1s.
y	A n*1 matrix, indicating the survival time;
cens	A n*1 matrix, consists of 0 and 1, 1 indicates that the row of data is censored, 0 is opposite.
alpha	Hyperparameter. The suggested value for alpha is 2 or 3.
itrNum	Maximum number of iteration steps. In general, 20 steps are enough.
thresh	Convergence threshold for beta Change, if max(abs(beta-beta_old))<threshold, return.
flag	It identifies whether to make model selection. The default is TRUE.
lamda_0	The initial value of the regularization parameter for ridge regression.
fdiag	It identifies whether to use diag Approximation to speed up the algorithm.
subItrNum	Maximum number of steps for subprocess iterations.

Value

Coefficient vector

GAGAs documentation built on May 29, 2024, 5:52 a.m.