Predictive Accuracy Gain From Disaggregate Sampling in ARIMA Models

Introduction to disaggregate demand models

Demand information is an input for a great deal of operations research models. Assumed as given in many problem instances addressed in the literature, demand data are di cult to generate. In this tutorial, we provide an introduction to disaggregate demand models that are designed to capture in detail the underlying behavioral mechanisms at the foundation of the demand.

Evaluating the Predictive Accuracy of Models Ray

Predictive accuracy for chaotic economic models

In this work we present a technique to obtain prediction intervals for chaotic data. Using nearest neighbors method we give estimates of local variance and percentiles of the prediction error distribution. This allows to define an interval containing a future value with a given probability. Its effectiveness is shown with data generated by a chaotic economic model.  2001 Elsevier Science B.V. ...

Examining Predictive Accuracy Among Discounting Models

Both descriptive and normative arguments claim that the discount rate to be applied to public projects should be elicited from individual intertemporal preferences. We present a methodology to analyze data from experimental surveys on intertemporal preferences. Focusing on the exponential and the hyperbolic discounting models, we model the experimental data published by Thaler (1981) by means o...

Investigating the accuracy of multivariate regression and ARIMA models in predicting water demand (Case Study: Mashhad city)

Awareness of water demand is of particular importance for its policy in urban management. Predicting water demand in the future will allow managers to take the necessary measures regarding sustainable water supply, given the constraints and crises ahead. The purpose of this study is to compare multivariate regression and ARIMA models to predict water demand in Mashhad. In this study, first, the...