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...

For statistical estimation problems, it is typical and even desirable that several reasonable estimators can arise for consideration. For example, the mean and median parameters of a symmetric distribution coincide, and so the sample mean and the sample median become competing estimators of the point of symmetry. Which is preferred? By what criteria shall we make a choice? One natural and time-...

We investigate the problem of estimating a random variable Y ∈ Y under a privacy constraint dictated by another correlated random variable X ∈ X , where estimation efficiency and privacy are assessed in terms of two different loss functions. In the discrete case, we use the Hamming loss function and express the corresponding utility-privacy tradeoff in terms of the privacy-constrained guessing ...

A polynomial approximation to the likelihood function allows for marginalised estimates of model parameters to be obtained in the form of a Volterra series. The series can be applied directly to the observed data vector in an iterative fashion, to converge upon a set of parameter MAP estimates with low computational cost. A sample application towards OCR is used as an illustration.

T his paper presents a new motion estimation algorithm to improve the performance of the existing searching algorithms at a relatively low computational cost. We try to amend the incorrect and/or inaccurate estimate of motion with higher precision by using Kalman filter. We first obtain a measurement of motion vector of a block by using the existing searching scheme. We then generate the predic...

We reconsider the classic problem of estimating accurately a 2D transformation from point matches between images containing outliers. RANSAC discriminates outliers by randomly generating minimalistic sampled hypotheses and verifying their consensus over the input data. Its response is based on the single hypothesis that obtained the largest inlier support. In this article we show that the resul...

Estimating computational cost is a fundamental issue in time-bounded computation. We present a method for estimating the hardness of optimisation problems (find a minimal cost solution to instance ) by observing that of the corresponding decision problems (has a solution of cost less than threshold ). Provided is not too close to the optimal, decision is typically much easier than optimisation,...

Pareto Density Estimation (PDE) as defined in this work is a method for the estimation of probability density functions using hyperspheres. The radius of the hyperspheres is derived from optimizing information while minimizing set size. It is shown, that PDE is a very good estimate for clusters of Gaussian structure. The robustness of the method is tested with respect to cluster overlap, number...

Many real-world applications share the property that the data they process arrives in streams. The transient and volatile nature of these streams renders the application of common processing and analysis techniques difficult. In particular, the mining of streams has proved to be a difficult task due to the rigid processing requirements that must be met within the data stream scenario. We propos...

In order to improve efficiency of video coding, temporal redundancy between neighboring frames can be reduced. In MPEG-2, some frames, named interframes, are predicted using a motion estimation based on the conservation of the intensity over time. In the new standard MPEG-4, frames are separated into several objects that are transmitted separately. Therefore, the prediction has to be performed ...