This study considers variance estimation when estimating the asymptotic variance of a propensity score matching estimator for the average treatment effect. We investigate the role of smoothing parameters in a variance estimator based on matching. We also study the properties of estimators using local linear estimation. Simulations demonstrate that large gains can be made in terms of mean square...

In a great deal of literature on fuzzy regression analysis, most of research has focused on some predefined parametric forms of fuzzy regression relationships, especially on the fuzzy linear regression models. In many practical situations, it may be unrealistic to predetermine a fuzzy parametric regression relationship. In this paper, a fuzzy nonparametric model with crisp input and LR fuzzy ou...

The Euler–Korteweg system consists of a quasi-linear, dispersive perturbation of the Euler equations. The Cauchy problem has been studied in any dimension d ≥ 1 by Benzoni, Danchin, and Descombes, who obtained local well-posedness results when the velocity is in Hs for s > d/2 + 1. They noticed that one may expect to find some smoothing effect due to the dispersive effects, but there was no pro...

Recently Chen and Mangasarian proposed a class of smoothing functions for linear/nonlinear programs and complementarity problems that uniies many previous proposals. Here we study a non-interior continuation method based on these functions in which, like interior path-following methods, the iterates are maintained to lie in a neighborhood of some path and, at each iteration, one or two Newton-t...

A local multilevel product algorithm and its additive version are analyzed for linear systems arising from the application of adaptive finite element methods to second order elliptic boundary value problems. The abstract Schwarz theory is applied to verify uniform convergence of local multilevel methods featuring Jacobi and Gauss-Seidel smoothing only on local nodes. By this abstract theory, co...

Regression analysis when the underlying regression function has jumps is a research problem with many applications. In practice, jumps often represent structure changes of a related process. Hence, it is important to detect them accurately from observed noisy data. In the literature, there are some jump detectors proposed, most of which are based on local constant or local linear kernel smoothi...

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the nonsimilar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (d...

This paper presents an Acoustic-to-Articulatory inversion method based on local regression. Two types of local regression, a non-parametric and a local linear regression have been applied on a corpus containing simultaneous recordings of positions of articulators and the corresponding acoustics. A maximum likelihood trajectory smoothing using the estimated dynamics of the articulators is also a...