Some aspects of the synchronization in coupled maps

Through numerical simulations we analyze the synchronization time and the Lyapunov dimension of a coupled map lattice consisting of a chain of chaotic logistic maps exhibiting power law interactions. From the observed behaviors we find a lower bound for the size $N$ of the lattice, independent of the range and strength of the interaction, which imposes a practical lower bound in numerical simulations for the system to be considered in the thermodynamic limit. We also observe the existence of a strong correlation between the averaged synchronization time and the Lyapunov dimension. This is an interesting result because it allows an analytical estimation of the synchronization time, which otherwise requires numerical simulations.Comment: 4 pages, 6 figure

Moderating Effects of Management Control Systems and Innovation on Performance. Simple Methods for Correcting the Effects of Measurement Error for Interaction Effects in Small Samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression.measurement error; interaction effects; disattenuation; small samples; moderated regression; reliability; Chronbach’s alpha