The Cramer-Rao error bound provides a fundamental limit on the expected performance of a statistical estimator. The error bound depends on the general properties of the system, but not on the specific properties of the estimator or the solution. The Cramer-Rao error bound has been applied to scalarand vector-valued estimators and recently to parametric shape estimators. However, nonparametric, ...

CH4 Parameter Estimation in CLM4.5bgc Using Surrogate Global Optimization J. Müller1, R. Paudel2, N. Mahowald2, and C.A. Shoemaker3 1Center for Computational Sciences and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720 2Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, 14853 3School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, 148...

(150 words) The notion of citizen driven development of public eservices has been vivid for a number of years in eGovernment research, practice and policies. A variety of expectations are coupled with the idea of citizens participating in the development process; ranging from, roughly outlined, more efficient services (economic gain and customer satisfaction) and enhanced democracy (deliberatio...

In this paper we consider a simple estimation problem on the special orthogonal group SO(n) and indicate a possible way to construct approximate filters which is much in the same spirit of the “wide sense” approach to linear filtering theory. Our interest is mainly motivated by applications to computer vision.

We study the general structure of the generalized Dirichlet distributions, deriving general formulas for the marginal and conditional probability density functions of those distributions. We develop the multivariate reverse rule properties of these distributions, apply those properties to derive probability inequalities, and derive stochastic representations and orderings for the distributions....

Introduction Where are we going? The Stochastic actor-oriented model Data and model definition Model specification Parameter interpretation Simulating network evolution Parameter estimation: MoM and MLE Extending the model: analyzing the co-evolution of networks and behavior Motivation Selection and influence Model definition and specification Simulating the co-evolution of networks and behavio...

Affine term structure models have gained significant attention in the finance literature, mainly due to their analytical tractability and statistical flexibility. The aim of this article is to present both theoretical foundations as well as empirical aspects of the affine model class. Starting from the original one-factor shortrate models of Vasiček and Cox et al, we provide an overview of the ...