Estimate the CSTE curve for time to event outcome with right censoring. The working model is $$\lambda(t| X, Z) = \lambda_0(t) \exp(\beta^T(X)Z + g(X)),$$ which implies that \(CSTE(x) = \beta(x)\).
cste_surv(x, y, z, s, h)samples of biomarker (or covariate) which is a \(n*1\) vector and should be scaled between 0 and 1.
samples of time to event which is a \(n*1\) vector.
samples of treatment indicator which is a \(n*K\) matrix.
samples of censoring indicator which is a \(n*1\) vector.
kernel bandwidth.
A \(n*K\) matrix, estimation of \(\beta(x)\).
Ma Y. and Zhou X. (2017). Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves, Statistical Methods in Medical Research, 26(1), 124-141.