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...

This paper shows that the bootstrap does not consistently estimate the asymptotic distribution of the maximum score estimator. The theory developed also applies to other estimators within a cube-root convergence class. For some single-parameter estimators in this class, the results suggest a...

We consider estimation of a linear or nonparametric additive model in which a few coefficients or additive components are “large†and may be objects of substantive interest, whereas others are “small†but not necessarily zero. The number of small coefficients or additive...

This paper analyses the constant elasticity of volatility (CEV) model suggested by Chan et al. (1992). The CEV model without mean reversion is shown to be the inverse Box-Cox transformation of integrated processes asymptotically. It is demonstrated that the maximum likelihood estimator of the...