Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...

This paper focuses on how to extend the exponential random graph models to take into account the ndogenous network processes

We study the sensitivity of election outcomes to small changes in voters’ preferences. We assume that a voter may err by swapping two adjacent candidates in his vote; we would like to check whether the election outcome would remain the same given up to δ errors. We show that this problem can be viewed as the destructive version of the unit-cost swap bribery problem, and demonstrate that it is p...

Federal law prohibits discrimination in employment decisions against persons in certain protected categories. The common method for measuring discrimination involves a comparison of some aggregate statistic for protected and non-protected individuals. This approach is open to question when employment decisions are made over an extended time period. We show how to use hierarchical proportional h...

Failure of economic models to anticipate the global financial crisis illustrates the need for modeling to better capture complex real-world dynamics. Conventional models—in which economic variables evolve toward equilibria or fluctuate about equilibria in response to exogenous random shocks—are ill-equipped to portray complex realworld dynamics in which economic variables may cycle aperiodicall...

Interest groups struggle to build reputations as influential actors in the policy process and to discern the influence exercised by others. This study conceptualizes influence reputation as a relational variable that varies locally throughout a network. Drawing upon interviews with 168 interest group representatives in the United States health policy domain, this research examines the effects o...

infiltration in furrow irrigation is 2-d which depends on both time and surface characteristics at which infiltration occurs. however, in many furrow irrigation models, infiltration is determined as a function of infiltration time opportunity, assuming the variation of weted perimeter is low along furrow. in order to compare the proposed asumptions, two zero-inertia furrow irrigation models wer...