Quantifying the historical range and variability of landscape composition and structure using simulation modeling is becoming an important means of assessing current landscape condition and prioritizing landscapes for ecosystem restoration. However, most simulated time series are generated using static climate conditions which fail to account for the predicted major changes in future climate. T...

In our project we have used parametric simulation and filtered historical simulation by GARCH processes to model the future position on a portfolio of some actively trading S&P bonds and related credit default swaps. The portfolio is marked to market daily based on the daily prices and CDS spreads over a seven year period. The Credit default swaps are priced daily based on the shifts in the def...

This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that controls bootstrap instability due to outlying observations. A Monte Carlo simulation shows that our robust method provides more accurate VaR fore...

This tutorial will identify and explore the essential techniques necessary for modern military training simulations. It will provide a brief historical introduction followed by discussions of system architecture; simulation interoperability; event and time management; distributed simulation; and verification, validation, and accreditation. This will be followed by fundamental principles in mode...

In this paper, we report the findings we gathered in designing and implementing a system that provides a distributed massive simulation environment. Massive Battle is a system capable of simulating historical battles for the purpose of learning and to carry out historical researches (e.g. what-if scenarios). We present a distributed implementation of Massive Battle and some early tests. We repo...

In order to postpone production planning based on information obtained close to the time of sale, decision support systems for supply chain management often include demand forecasts based on little historical data and/or subjective information. Particularly, when simulation models for analyzing decisions related to safety inventories, lot sizing or lead times are used, it is convenient to model...

There are two types of simulation models: Demonstration models, essentially existence proofs for phenomena of interest, and Descriptive models, that attempt to track dynamic historical phenomena. Both types require verification. Descriptive models require validation against historical data as well. More broadly, we can think of a process of choosing the “best” of several models. This paper exam...

Spatially-explicit land cover land use change (LCLUC) models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption t...