Regression Method for ph Class
# S4 method for ph
reg(
x,
y,
weight = numeric(0),
rcen = numeric(0),
rcenweight = numeric(0),
X = numeric(0),
B0 = numeric(0),
stepsEM = 1000,
methods = c("RK", "UNI"),
rkstep = NA,
uni_epsilon = NA,
optim_method = "BFGS",
maxit = 50,
reltol = 1e-08,
every = 10
)
vector or data.
vector of weights.
vector of right-censored observations
vector of weights for right-censored observations.
model matrix (no intercept needed).
initial regression coefficients (optional).
number of EM steps to be performed.
methods to use for matrix exponential calculation: RM, UNI or PADE
Runge-Kutta step size (optional)
epsilon parameter for uniformization method
method to use in gradient optimization
maximum number of iterations when optimizing g function.
relative tolerance when optimizing g function.
number of iterations between likelihood display updates.