Multiple integrals encountered when evaluating posterior densities in Bayesian estimation were approximated using Multivariate Gaussian Quadrature (MGQ). Experimental results for a linear regression model suggest MGQ provides better approximations to unknown parameters and error variance than simple Monte Carlo based approximations. The authors are Graduate Research Assistant, Professor and Gra...

DeMiguel, Garlappi, and Uppal (Review of Financial Studies, 22 (2009), 1915–1953) showed that in the stock market, it is difficult for an optimized portfolio constructed using meanvariance analysis to outperform a simple equally-weighted portfolio because of estimation error. In this paper, we demonstrate that portfolio optimization can be made to work in currency markets. The key difference be...

Parameter estimation of polynomial phase signals (PPSs) is of great interest in various practical applications. In this paper, parametric methods for parameter estimation of polynomial phase signals are discussed and compared. The suboptimal maximum likelihood estimation methods, such as the high-order ambiguity function (HAF) and the product HAF (PHAF) are presented. The polynomial time freque...

A fundamental problem in order selection is that one single realization of a stochastic process is used twice, for the estimation of parameters for different model orders and for the selection of the best model order. Parameters are estimated by the minimization of the residual variance; higher model orders with more estimated parameters will always give a smaller residual variance. The purpose...

due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. the known world class cu-mo deposit, sarcheshmeh porphyry deposit (central iran) selected as the study area. the hypogene zone of the deposit was chosen as the space in which estim...

due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. the known world class cu-mo deposit, sarcheshmeh porphyry deposit (central iran) selected as the study area. the hypogene zone of the deposit was chosen as the space in which estim...

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 variablesta...

In this paper, we address the risk-sensitive filtering problem which is minimizing the expectation of the exponential of the squared estimation error multiplied by a risk-sensitive parameter. Such filtering can be more robust to plant and noise uncertainty than minimum error variance filtering. Although optimizing a differently formulated performance index to that of the so-called H1 filtering,...

a method for error estimation of isogeometric analysis of plane stress problems which is the based on stress recovery and using the super convergent properties of the gauss points, has been already introduced. this paper is devoted to the development of the method and study of the effects of these supercovergent points on the solution improvement and error estimation of axisymmetric problems by...