Markov chain theory is proving to be a powerful approach to bootstrap highly nonlinear time series. In this work we provide a method to estimate the memory of a Markov chain (i.e. its order) and to identify its relevant states. In particular the choice of memory lags and the aggregation of...

Consider a finite-state Markov chain where the transition probabilities differ by orders of magnitude. This Markov chain has an "attractor state," i.e., from any state of the Markov chain there exists a sample path of significant probability to the attractor state. There also exists a "rare...

The research, through a bidirectional approach, aims to develop the university management of the degree programs in order to attract and maintain the potential students, as well as to estimate and manage the costs of the educational services offered during their life cycle. The authors bring...

Mathematical programming representation has been recently used to describe the behavior of discrete event systems as well as their formal properties. This new way of representing discrete event systems paves the way to the creation of simpler mathematical programming models that reduce the...

Four strategies for farm growth are analyzed and compared on the basis of ownership, equity, and productive capacity achieved, and on the basis of resistance to adversity. The primary tool of analysis was a model utilizing a stochastic simulator interfaced with both ex ante and ex post linear...