Apart from kernel estimators, there have been quite a few different approaches of “generalized splines” for density estimation. In the present paper,Maximum Penalized Likelihood (mpl) approaches are reviewed. In conclusion, penalizing the log density seems most promising. In my “wp” approach for semi-parametric density estimation, a novel roughness penalty is introduced. It penalizes a relative...

OBJECTIVE To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contracept...

8 Efron (1979) introduced the bootstrap method for independent data but it can not be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block bootstrap method is usually used to estimate the precision measures of the estimators. The precision of the moving block bootstrap estimators is ...

8 Efron (1979) introduced the bootstrap method for independent data but it can not be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block bootstrap method is usually used to estimate the precision measures of the estimators. The precision of the moving block bootstrap estimators is ...

We review estimation in interval censoring models, including nonparametric estimation of a distribution function and estimation of regression models. In the non-parametric setting, we describe computational procedures and asymptotic properties of the nonparametric maximum likelihood estimators. In the regression setting, we focus on the proportional hazards, the proportional odds and the accele...

many empirical papers have applied a semi-parametric two-stage procedure named tobit model to investigate the sources of inefficiency in different industries over the last two decades. using this approach in small samples has recently been criticized for a possible bias in its results. in very recent papers simar and wilson (2007) have tackled this problem by suggesting an alternative bootstrap...