Besides being an ill-posed problem, the pel-recursive computation of 2-D optical flow raises a wealth of issues, such as the treatment of outliers, motion discontinuities and occlusion. Our proposed approach deals with these issues within a common framework. It relies on the use of a data-driven technique called Generalized Cross Validation (GCV) to estimate the best regularization scheme for a...

It has been shown that space-variant regularization in image restoration provides better results than space-invariant regularization. However, the optimal choice of the regularization parameter is usually unknown a priori. In previous work, the generalized cross-validation (GCV) criterion was shown to provide accurate estimates of the optimal regularization parameter. The author introduces a mo...

Generalized Cross Validation (GCV) is a popular approach to determining the regularization parameter in Tikhonov regularization. The regularization parameter is chosen by minimizing an expression, which is easy to evaluate for small-scale problems, but prohibitively expensive to compute for large-scale ones. This paper describes a novel method, based on Gauss-type quadrature, for determining up...

Projection pursuit regression (PPR) can be used to estimate a smooth function of several variables from noisy and scattered data. The estimate is a sum of smoothed one-dimensional projections of the variables. This paper discusses an extension of PPR to exponential family distributions, called generalized projection pursuit regression (GPPR). The proposed model allows multiple responses and non...

This article considers testing the hypothesis of Generalized Linear Models (GLM) versus general smoothing spline models for data from exponential families. The tests developed are based on the connection between smoothing spline models and Bayesian models (Gu (1992)). They are extensions of the locally most powerful (LMP) test of Cox, Koh, Wahba and Yandell (1988), the generalized maximum likel...

In Central Lombok Regency, the hotel tax is one of highest incomes contributing to Regional Original Revenue. A a on services provided by hotel. This research aims estimate nonparametric kernel regression curve revenue data in Lombok. The method used analysis with seven functions. results Generalized Cross Validation (GCV) criteria, optimal bandwidth values ​​generated functions have varying va...

In this paper, we propose a Generalized Approximate Cross Validation (GACV) function for estimating the smoothing parameter in the penalized log likelihood regression problem with non-Gaussian data. This GACV is obtained by, first, obtaining an approximation to the leaving-out-one function based on the negative log likelihood, and then, in a step reminiscent of that used to get from leaving-out...

Nonparametric regression approaches are used when the shape of curve between response variable and predictor is assumed to be unknown. excess has high flexibility. A frequently nonparametric approach a truncated spline that excellent ability handle data whose behavior at certain sub-intervals. The aim this study was obtain best model multivariable with linear quadratic using Generalized Cross V...

Nonparametric regression models are often used to check or suggest a parametric model. Several methods have been proposed to test the hypothesis of a parametric regression function against an alternative smoothing spline model. Some tests such as the locally most powerful (LMP) test by Cox et al. (Cox, D., Koh, E., Wahba, G. and Yandell, B. (1988). Testing the (parametric) null model hypothesis...

In variational data assimilation, optimal ingestion of the observational data and optimal use of prior physical and statistical information involve the choice of numerous weighting, smoothing and tuning parameters which control the ltering and merging of divers sources of information. Generally these weights must be obtained from a partial and imperfect understanding of various sources of error...