In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise....

Diffusion modeling is rather broad in nature, and is important in the areas of estimation and forecasting. Conventional models do not incorporate parameters that explicitly take into account the size of the population, or, equivalently, the size of the potential market. As a consequence, the...

In our prior work on product diffusions in presence of a capacity constraint, we postulated that a firm operating in such an environment should always attempt to fulfill as much of the present demand as is possible with the capacity constraint. In other words, the firm would never have demand...

This article discusses the expansion of credit cards in Taiwan. The intention of the study is (1) to compare the performance of various diffusion models, such as logistic models, Fourier models and autoregressive models; (2) to identify the important explanatory factors regarding the expansion...

A new model, based on an asymptotic procedure for solving the generalized kinetic equations of electrons and phonons, is proposed. The linearized equations turn out to be solvable and lead naturally to the displaced Maxwellian approximation. The constitutive laws for the electric and thermal...

We introduce a functional volatility process for modeling volatility trajectories for high frequency observations in financial markets and describe functional representations and data-based recovery of the process from repeated observations. A study of its asymptotic properties, as the frequency...