We study nonparametric likelihood-based estimators of the mean function of counting processes with panel count data using monotone polynomial splines. The generalized Rosen algorithm, proposed by Zhang & Jamshidian (2004), is used to compute the estimators. We show that the proposed spline...

We propose a spline-based semiparametric maximum likelihood approach to analysing the Cox model with interval-censored data. With this approach, the baseline cumulative hazard function is approximated by a monotone B-spline function. We extend the generalized Rosen algorithm to compute the...

We study a spline-based likelihood method for the partly linear model with monotonicity constraints. We use monotone B-splines to approximate the monotone nonparametric function and apply the generalized Rosen algorithm to compute the estimators jointly. We show that the spline estimator of the...