Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.

Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data,...

Chapter 1 System Science -- Chapter 2 Decision-Making Methods -- Chapter 3 Prediction Methods -- Chapter 4 Evaluation Methods -- Chapter 5 Optimization Algorithm -- Chapter 6 System Reliability -- Chapter 7 Game Theory -- Chapter 8 Management Simulation -- Chapter 9 Complexity Science.-Chapter...

Chapter 1. A disaggregate hierarchical decision Huff model incorporating consumer Kaiyu choices among shopping sites -- Chapter 2. A dynamical Huff model: Computing the competitive equilibrium distribution of shop floor areas over a city center commercial district using the Fixed-Point Algorithm...