Finding Expectations of Monotone Functions of Binary Random Variables by Simulation, with Applications to Reliability, Finance, and Round Robin Tournaments

Author(s):  
Mark Brown ◽  
Erol A. Peköz ◽  
Sheldon M. Ross
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.


2021 ◽  
pp. 004912412110312
Author(s):  
Martina Raggi ◽  
Elena Stanghellini ◽  
Marco Doretti

The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual term that vanishes under some specific conditions. We then extend our definitions to situations involving multiple mediators and address research questions concerning the decomposition of the total effect when some mediators on the pathway from the treatment to the outcome are marginalized over. Connections to the counterfactual definitions of the effects are also made. Data coming from an encouragement design on students’ attitude to visit museums in Florence, Italy, are reanalyzed. The estimates of the defined quantities are reported together with their standard errors to compute p values and form confidence intervals.


2009 ◽  
Vol 36 (3) ◽  
pp. 837-852 ◽  
Author(s):  
Dirk Briskorn ◽  
Andreas Drexl

1966 ◽  
Vol 73 (3) ◽  
pp. 231-246 ◽  
Author(s):  
Frank Harary ◽  
Leo Moser

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