In the image parameter estimation by the linear regression, it has very high degrees of freedom for the decision of regression coefficients, because the dimension of image vector is huge high. In this paper, we discuss its potential by the learning of the dense samples. For the learning process, we employed a sequential regression coefficient calculation algorithm and realize its calculation fo...

We discuss the classical efficiency criteria in density estimation and propose some variants. The context is a general density estimation scheme that contains the cases of i.i.d. or dependent random variables, in discrete or continuous time. Unbiased estimation, optimality and asymptotic optimality are considered. An example of a density estimator that satisfies some suggested criteria is given...

We develop a generally applicable framework for constructing efficient estimators of regression models via quantile regressions. The proposed method is based on optimally combining information over multiple quantiles and can be applied to a broad range of parametric and nonparametric settings. When combining information over a fixed number of quantiles, we derive an upper bound on the distance ...

The Pareto distribution is a simple model for nonnegative data with a power law probability tail. In many practical applications, there is a natural upper bound that truncates the probability tail. This paper derives estimators for the truncated Pareto distribution, investigates their properties, and illustrates a way to check for fit. We illustrate these methods with applications from finance,...

We discuss structuralmodels based onMerton’s framework. First, we observe that the classical assumptions of theMertonmodel are generally rejected. Secondly, we implement a structural credit riskmodel based on stable non-Gaussian processes as a representative of subordinated models in order to overcome some drawbacks of the Merton one. Finally, following the KMV-Merton estimation methodology, we...

Dominant motion estimation in video sequence is a task that must be often be solved in Computer Vision problems but involves a high computational cost due to the overwhelming amount of data to be treated when working in image domain. In this paper we introduce a novel technique to perform motion analysis in video sequences taking advantage of the motion information of MPEG streams and its struc...

this paper is concerned with the estimation of frontier production function to measure the technical efficiency for iranian textile companies during 1995. the objective of this estimation is to investigate if there are any differences in the technical efficiency between the private and public firms as well as the relationship between technical efficiency and size of textile companies in iran. a...