Quantifying stochastic outcomes.

Conceptual Issues in Quantifying Unusualness and Conceiving Stochastic Experiments: Insights from Students’ Experiences in Designing Sampling Simulations1

This article reports on a classroom teaching experiment that engaged a group of high school students in designing sampling simulations within a computer microworld. The simulation-design activities aimed to foster students’ abilities to conceive of contextual situations as stochastic experiments, and to engage them with the logic of hypothesis testing. This scheme of ideas involves imagining a ...

Demand-oriented timetable design for urban rail transit under stochastic demand

In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its va...

Fuzzy completion time for alternative stochastic networks

In this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. In other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of network. Then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (TFN). This paper com...

Enhanced coding for exponentially distributed signals using suprathreshold stochastic resonance

Our previous work on stochastic resonance (SR) in threshold based systems proved that the SR effect is dependent on the nature of the input signal distribution; more specifically, for certain types of signal distribution SR is not observed [Das A, Stocks NG, Nikitin A, Hines EL. Quantifying stochastic resonance in a single threshold detector for random aperiodic signals. Fluctuation Noise Lett ...

Quantifying Our Ignorance: Stochastic Forecasts of Population and Public Budgets

The behavior of the reliability functions and stochastic orders in family of the Kumaraswamy-G distributions

The Kumaraswamy distribution is a two-parameter distribution on the interval (0,1) that is very similar to beta distribution. This distribution is applicable to many natural phenomena whose outcomes have lower and upper bounds, such as the proportion of people from society who consume certain products in a given interval.  In this paper, we introduce the family of Kumaraswamy-G distribution, an...