bssmle: B-spline Sieve Maximum Likelihood Estimation
Description
Routine that performs B-spline sieve maximum likelihood estimation with linear and nonlinear inequality constraints
Usage
bssmle(formula, data, alpha)
Arguments
formula
a formula object relating survival object Surv2(v, u, event) to a set of covariates.
data
a data frame to be used.
alpha
\(\alpha = (\alpha1, \alpha2)\) contains parameters that define the link functions from class of generalized odds-rate transformation models. The components \(\alpha1\) and \(\alpha2\) should both be \(\ge 0\). If \(\alpha1 = 0\), the user assumes a proportional subdistribution hazards or Fine-Gray model for cause of failure 1. If \(\alpha2 = 1\), the user assumes a proportional odds model for cause of failure 2.
Value
The function bssmle returns a list of components:
beta
a vector of the estimated coefficients for the B-splines
varnames
a vector containing variable names
alpha
a vector of the link function parameters
loglikelihood
a loglikelihood of the fitted model
convergence
an indicator of convegence
tms
a vector of the minimum and maximum observation times
Bv
a list containing the B-splines basis functions evaluated at v
Details
The function bssmle performs B-spline sieve maximum likelihood estimation.