Parametric statistics

About: Parametric statistics is a research topic. Over the lifetime, 39200 publications have been published within this topic receiving 765761 citations.

Semiparametric Estimation of Selection Models: Some Empirical Results

Abstract: Among the central theoretical developments in the econometric analysis of nonexperimental microeconomic data has been the analysis of selectivity bias. Following the work of James Heckman (1974), statistical techniques were developed in the 1970s to consistently estimate the parameters of these models. One potential drawback to the application of these techniques is their sensitivity to the assumed parametric distribution of the unobservable error terms in the model. In recent years, a number of estimation methods for selection models have been developed which do not impose parametric forms on error distributions; these methods are termed "semiparametric," since only part of the model of interest (the regression function) is parametrically specified. While the statistical theory of these semiparametric estimators has received much attention, practical applications of the methods are lacking (an exception being the paper by Joel Horowitz and George Neumann, 1987). In this paper, we use semiparametric methods to reanalyze data on the labor supply of married women first studied by Thomas Mroz (1987) using parametric methods. The object of this reanalysis is to determine whether Mroz's results are sensitive to his parametric assumptions.

Parameterization-free projection for geometry reconstruction

Abstract: We introduce a Locally Optimal Projection operator (LOP) for surface approximation from point-set data. The operator is parameterization free, in the sense that it does not rely on estimating a local normal, fitting a local plane, or using any other local parametric representation. Therefore, it can deal with noisy data which clutters the orientation of the points. The method performs well in cases of ambiguous orientation, e.g., if two folds of a surface lie near each other, and other cases of complex geometry in which methods based upon local plane fitting may fail. Although defined by a global minimization problem, the method is effectively local, and it provides a second order approximation to smooth surfaces. Hence allowing good surface approximation without using any explicit or implicit approximation space. Furthermore, we show that LOP is highly robust to noise and outliers and demonstrate its effectiveness by applying it to raw scanned data of complex shapes.

Robust sliding-mode control for uncertain time-delay systems: an LMI approach

Abstract: This note is devoted to robust sliding-mode control for time-delay systems with mismatched parametric uncertainties. A delay-independent sufficient condition for the existence of linear sliding surfaces is given in terms of linear matrix inequalities, based on which the corresponding reaching motion controller is also developed. The results are illustrated by an example.

Reliability Theory: With Applications to Preventive Maintenance

Abstract: 1 System Reliability as a Function of Component Reliability.- 2 Parametric Lifetime Distributions.- 3 Statistical Inference from Incomplete Data.- 4 Preventive Maintenance Models Based on the Lifetime Distribution.- 5 Preventive Maintenance Based on Parameter Control.- 6 Best Time Scale for Age Replacement.- 7 Preventive Maintenance with Learning.- Solutions to Exercises.- Appendix A: Nonhomogeneous Poisson Process.- A.1 Definition and Basic Properties.- A.2 Parametric estimation of the intensity function.- Appendix B: Covariances and Means of Order Statistics.- Appendix C: The Laplace Transform.- Appendix D: Probability Paper.- Appendix E: Renewal Function.- References.- Glossary of Notation.