Structural system identification methods are analytical techniques for reconciling test data with analytical models. The response data frequently used to compare a finite element model and test data are the eigenvalues of the system. However, eigenvalues alone cannot assure an adequate model....

This paper investigates extensions of the method of endogenous gridpoints (ENDGM) introduced by Carroll (2006) to higher dimensions with more than one continuous endogenous state variable. We compare three different categories of algorithms: (i) the conventional method with exogenous grids...

Over the past several decades, the development of computer models to predict the atmospheric transport of hazardous material across a local (on the order of 10s of km) to mesoscale (on the order of 100s of km) region has received considerable attention, for both regulatory purposes, and to guide...

The mechanics of the flowing granular materials such as coal, agricultural products, at deal of attention as it has fertilizers, dry chemicals, metal ores, etc. have received a great deal of attention as it has relevance to several important technological problems. Despite wide interest and more...

Current practice uses statistical tests to determine whether seasonal factors should be applied in a given forecasting situation. Research suggests that an optimal policy might lie somewhere between using full seasonal factors and using no seasonal factors on series. This research proposes and...

We derive the well-known continuity principle for adjoint variables for preannounced or anticipated changes in parameters for continuoustime, infinite-horizon, perfect foresight optimization models. For easy and intuitive numerical computation of the resulting multi point boundary value problem...

This paper introduces a behavioural model and an algorithm that allow define classes of investors and draw the size each of them from financial data. The nonparametric pricing kernel estimated from stocks and options quotes allows to derive an estimate of the market utility. At the micro level...

This article deals with practical problems of fitting empirical data with generalized lambda distribution. Given method based on moment matching is illustrated on a practical example.

We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (DDC) models. We use importance sampling to approximate the Bellman operators defining the two functions. The random...