Search results for "Minimum-variance unbiased estimator"
showing 4 items of 14 documents
New Results in Generalized Minimum Variance Control of Computer Networks
2014
In this paper new results in adaptive (generalized) minimum variance control of packet switching computer networks are presented. New solutions, corresponding to the new inverses of the nonsquare polynomial matrices, can be used for design of robust control of multivariable systems with different number of inputs and outputs. Application of polynomial matrix inverses with arbitrary degrees of freedom creates the possibilities to optimal control of computer networks in terms of usage their maximal bandwidth. Simulation examples made in Matlab environment show big potential of presented approach. DOI: http://dx.doi.org/10.5755/j01.itc.43.3.6268
Variance Estimation and Asymptotic Confidence Bands for the Mean Estimator of Sampled Functional Data with High Entropy Unequal Probability Sampling …
2013
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the Hajek formula. The interest of this asymptotic variance approximation is that it only involves the first order inclusion probabilities of the statistical units. We extend this variance formula when the variable under study is functional and we prove, under general conditions on the regularity of the individual trajectories and the sampling design, that it asymptotically provides a uniformly consistent estimator of the variance function of the Horvitz-Thompson estimator of the mean function. Rates of convergence to the true variance function are gi…
Uniform convergence and asymptotic confidence bands for model-assisted estimators of the mean of sampled functional data
2013
When the study variable is functional and storage capacities are limited or transmission costs are high, selecting with survey sampling techniques a small fraction of the observations is an interesting alternative to signal compression techniques, particularly when the goal is the estimation of simple quantities such as means or totals. We extend, in this functional framework, model-assisted estimators with linear regression models that can take account of auxiliary variables whose totals over the population are known. We first show, under weak hypotheses on the sampling design and the regularity of the trajectories, that the estimator of the mean function as well as its variance estimator …
Combining Defocus and Photoconsistency for Depth Map Estimation in 3D Integral Imaging
2017
This paper presents the application of a depth estimation method for scenes acquired using a Synthetic Aperture Integral Imaging (SAII) technique. SAII is an autostereoscopic technique consisting of an array of cameras that acquires images from different perspectives. The depth estimation method combines a defocus and a correspondence measure. This approach obtains consistent results and shows noticeable improvement in the depth estimation as compared to a minimum variance minimisation strategy, also tested in our scenes. Further improvements are obtained for both methods when they are fed into a regularisation approach that takes into account the depth in the spatial neighbourhood of a pix…