Identification of Multiple First-Order Continuous-Time Dynamic Models From Special Segments in Historical Data

Identification of Continuous-time Models from Sampled Data

First order linear fuzzy dynamic equations on time scales

In this paper, we study the concept of generalized differentiability for fuzzy-valued functions on time scales. Usingthe derivative of the product of two functions, we provide solutions to first order linear fuzzy dynamic equations. Wepresent some examples to illustrate our results.

First-Order Continuous Models of Opinion Formation

We study certain nonlinear continuous models of opinion formation derived from a kinetic description involving exchange of opinion between individual agents. These models imply that the only possible final opinions are the extremal ones, and are similar to models of pure drift in magnetization. Both analytical and numerical methods allow to recover the final distribution of opinion between the ...

Identification of Continuous Time Rational Expectations Models from Discrete Time Data

III' This paper proves two propositions about identification in a continuous time version of a linear stochastic rational expectations model. The model is a continuous time version of Lucas and Prescott (1971), in which'the equilibrium can be interpreted.~ the solution of a 'stochastic control problem, either of a collection of private agents or of a fictitious "socialplanner. Estimation is dir...

Continuous Time Dynamic Topic Models

In this paper, we develop the continuous time dynamic topic model (cDTM). The cDTM is a dynamic topic model that uses Brownian motion to model the latent topics through a sequential collection of documents, where a “topic” is a pattern of word use that we expect to evolve over the course of the collection. We derive an efficient variational approximate inference algorithm that takes advantage o...