A Two-Stage Estimation Approach to Cox Regression Using M-Spline Function
Maximum likelihood estimation for spline copula parameter matrix
B-spline copula using the five M-spline basis functions
Random generation from the B-spline copula using five M-spline basis f...
Fitting the five-parameter spline Cox model giving a specified shape
Fitting the five-parameter spline Cox model with a specified shape, se...
Implements a two-stage estimation approach for Cox regression using five-parameter M-spline functions to model the baseline hazard. It allows for flexible hazard shapes and model selection based on log-likelihood criteria as described in Teranishi et al.(2025). In addition, the package provides functions for constructing and evaluating B-spline copulas based on five M-spline or I-spline basis functions, allowing users to flexibly model and compute bivariate dependence structures. Both the copula function and its density can be evaluated. Furthermore, the package supports computation of dependence measures such as Kendall's tau and Spearman's rho, derived analytically from the copula parameters.