MoE-ph-method: MoE method for ph Class

In matrixdist: Statistics for Matrix Distributions

MoE method for ph Class

Description

MoE method for ph Class

Usage

## S4 method for signature 'ph'
MoE(
  x,
  formula,
  data,
  inhom = NULL,
  alpha_vecs = NULL,
  weight = numeric(0),
  delta = numeric(0),
  stepsEM = 1000,
  optim_method = "BFGS",
  maxit = 50,
  reltol = 1e-08,
  every = 10,
  rand_init = TRUE
)

Arguments

x	An object of class ph.
formula	A regression formula.
data	A data frame.
inhom	A list with the inhomogeneity functions.
alpha_vecs	Matrix of initial probabilities.s
weight	Vector of weights.
delta	Right-censoring indicator.
stepsEM	Number of EM steps to be performed.
optim_method	Method to use in gradient optimization.
maxit	Maximum number of iterations when optimizing g function.
reltol	Relative tolerance when optimizing g function.
every	Number of iterations between likelihood display updates.
rand_init	Random initiation in the R-step.

Value

An object of class sph.

Examples

x <- iph(ph(structure = "general"), gfun = "weibull")
n <- 100
responses <- rweibull(n, 2, 3)
covariate <- data.frame(age = sample(18:65, n, replace = TRUE) / 100, income = runif(n, 0, 0.99))
f <- responses ~ age + income # regression formula
MoE(x = x, formula = f, y = responses, data = covariate, stepsEM = 20)

matrixdist documentation built on Aug. 8, 2023, 5:06 p.m.