BACKGROUND Case-control studies are useful for rare outcomes, but typical analyses limit investigators to parametric estimation of conditional odds ratios. Several methods exist for obtaining marginal risk differences and risk ratios in a case-control setting, including a recently described semiparametric targeted approach optimized for rare outcomes. METHODS Using case-control data from a st...

5 Warranty claims reported in recent months might carry more up-to-date information than 6 those reported in earlier months. Using weighted maximum likelihood estimation for esti7 mating model parameters might therefore lead to better performance of warranty forecast8 ing models than maximum likelihood estimation. This paper examines this issue and also 9 presents comparison of the forecasting ...

................................................................................................... 2 INTRODUCTION............................................................................................ 3 SOFTWARE ESTIMATION AN OVERVIEW ............................................................................................... 3 INDUSTRY FOLLOWED ESTIMATION MECHANISMS .....................

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...

We introduce an extended data-model for high resolution channel parameter estimation and parametric channel modeling. Other than the well-known ray-optical based data models which contain only discrete (specular) propagation paths, we additionally introduce distributed diffuse scattering components. To this end a simple parametric data model of the diffuse scattering distribution in the delay d...

We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimato...

The Finite Sample Performance of Semiand Nonparametric Estimators for Treatment Effects and Policy Evaluation This paper investigates the finite sample performance of a comprehensive set of semiand nonparametric estimators for treatment and policy evaluation. In contrast to previous simulation studies which mostly considered semiparametric approaches relying on parametric propensity score estim...

Non-parametric density estimation has broad applications in computational nance especially in cases where high frequency data are available. However, the technique is often intractable , given the run times necessary to evaluate a density. We present a new and eecient algorithm based on multipole techniques. Given the n kernels that estimate the density, current methods take O(n) time to direct...

The objective of Empirical Software Engineering is to improve the software development and maintenance processes and consequently the quality of theirs various deliverables. This can be achieved by evaluating, controlling and predicting some important attributes of software projects such as development effort, software reliability, and programmers productivity. One of the most interesting sub-f...

Non-parametric density estimation has broad applications in computational nance especially in cases where high frequency data are available. However, the technique is often intractable , given the run times necessary to evaluate a density. We present a new and eecient algorithm based on multipole techniques. Given the n kernels that estimate the density, current methods take O(n) time to direct...