A posteriori estimation of the numerical error sensitivity to the local truncation error is addressed using adjoint model endowed with the information on the error field. The numerical error is estimated from the solution of the linear tangent model (LTM) or from a Richardson extrapolation. The local truncation error used in the LTM is obtained by the action of a high order finite-difference st...

We propose a new wavelet domain image interpolation scheme based on statistical signal estimation. A linear composite MMSE estimator is constructed to synthesize the detailed wavelet coefficients as well as to minimize the mean squared error for high-resolution signal recovery. Based on a discrete time edge model, we use low-resolution information to characterize local intensity changes and per...

Background and objectives: Risk-adjusted Bernoulli control chart is one of the main tools for monitoring multistage healthcare processes to achieve higher performance and effectiveness in healthcare settings. Using parameter estimates can lead to significantly deteriorate chart performance. However, so far, the effect of estimation error on this chart in which healthcare ...

Prediction error is critical to assessing the performance of statistical methods and selecting statistical models. We propose the cross-validation and approximated cross-validation methods for estimating prediction error under a broad q-class of Bregman divergence for error measures which embeds nearly all of the commonly used loss functions in regression, classification procedures and machine ...

This paper considers a class of semiparametric models being the sum of a nonparametric trend function g and a FARIMA-GARCH error process. Estimation of g( ), the th derivative of g, by local polynomial tting is investigated. The focus is on the derivation of the asymptotic normality of ĝ( ). At rst a central limit theorem based on martingale theory is developed and asymptotic normality of the s...

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

We present a general-purpose meta-generalized gradient approximation (MGGA) exchange-correlation functional generated within the Bayesian error estimation functional framework [J. Wellendorff, K. T. Lundgaard, A. Møgelhøj, V. Petzold, D. D. Landis, J. K. Nørskov, T. Bligaard, and K. W. Jacobsen, Phys. Rev. B 85, 235149 (2012)]. The functional is designed to give reasonably accurate density func...

One of the important issues in many of array systems such as Radar, Sonar, Mobile, and satellite telecommunications is the estimation of DOA of narrowband received signal. CRB is very important in evaluation of parameter estimation. CRB is the lower bound estimation error variance for any unbiased estimation. In this paper, the array antenna with equal distance arrays is extended in two separat...

Numerical error estimation for time dependent hyperbolic problems is challenging for theoretical and practical reasons. In these systems, error can propagate long distances and produce effects far from the point of generation. In addition, nonlinear interactions of error, as well as discretization nonlinearities can play important roles and must be addressed. In this work, we investigate the us...

in this paper at first , we discuss about nonlinear pseudoparabolic equations with nonlocalboundary conditions and their results.at second we use an effective error estimation for this method altough has not yet beendiscussed. the aim of this paper is to fill this gap.