assimilation method. It applies an ensemble of model states to represent the error statistics ... model estimate, it applies ensemble integrations to predict the error statistics forward in time ... which operates directly on the ensemble of model states when observations are assimilated. The EnKF ... used in realistic applications with primitive equation models for the ocean and atmosphere. A recent...
Computational Fluid Dynamics (CFD) code for modelling fluid flow, heat transfer, mass transfer and chemical ... option enables the incorporation of user-developed models into FLUENT through user-defined functions.32...
NuSMV is a symbolic model checker developed as a joint project between: The Embedded Systems ... Information Technology at FBK-IRST The Model Checking group at Carnegie Mellon University , the Mechanized ... reimplementation and extension of SMV, the first model checker based on BDDs. NuSMV has been ... designed to be an open architecture for model checking, which can be reliably used...
last thirty eight years, the LISREL model, methods and software have become synonymous with structural ... equation modeling (SEM). SEM allows researchers in the social sciences, management sciences, behavioral sciences, biological ... These theories are usually formulated as theoretical models for observed and latent (unobservable) variables ... observed variables of the theoretical model, the LISREL program can be used...
study of discrete event systems modeled by finite-state automata (FSA). There are routines ... consulted for an introduction to modeling of discrete event systems by FSA’s, manipulation ... models, and the theory of supervisory control of discrete event systems...
Univariate and Multivariate Hierarchical Point-referenced Spatial Models. Scientists and investigators in such diverse fields ... often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves computationally intensive Markov ... wide variety of Gaussian spatial process models for univariate as well as multivariate point-referenced...
Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze ... Mplus offers researchers a wide choice of models, estimators, and algorithms in a program that ... analyzed according to any of the models included in the program...
structure in an undirected Gaussian graphical model, using ℓ 1 regularization to control the number ... efficiently build a path of models for different values of the tuning parameter. Convergence...
Network and discrete location. Models, algorithms, and applications (to appear) The second edition focuses ... real-world extensions of the basic models used in locating facilities, including production and distribution ... systems, location-inventory models, and defender-interdictor problems. A unique taxonomy of location problems ... models is also presented. Featuring examples using the author’s own software -- SITATION, MOD-DIST...
Network and discrete location. Models, algorithms, and applications (to appear) The second edition focuses ... real-world extensions of the basic models used in locating facilities, including production and distribution ... systems, location-inventory models, and defender-interdictor problems. A unique taxonomy of location problems ... models is also presented. Featuring examples using the author’s own software -- SITATION, MOD-DIST...
package ismev: An Introduction to Statistical Modeling of Extreme Values. Functions to support the computations ... carried out in ‘An Introduction to Statistical Modeling of Extreme Values’ by Stuart Coles...
Network and discrete location. Models, algorithms, and applications (to appear) The second edition focuses ... real-world extensions of the basic models used in locating facilities, including production and distribution ... systems, location-inventory models, and defender-interdictor problems. A unique taxonomy of location problems ... models is also presented. Featuring examples using the author’s own software -- SITATION, MOD-DIST...
Smoothing spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing ... settings number far less. Smoothing spline ANOVA models are a versatile family of smoothing methods ... likelihood method and the construction of multivariate models with built-in ANOVA decompositions. Extensive discussions ... devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational...