A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay case study

2019 ◽  
Vol 118 ◽  
pp. 1-13 ◽  
Author(s):  
Rebecca R. Murphy ◽  
Elgin Perry ◽  
Jon Harcum ◽  
Jennifer Keisman
Keyword(s):  
Water Quality ◽  
Chesapeake Bay ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Model Approach

Integrating multiple data sources in match-fixing warning systems

2018 ◽  
Vol 18 (5-6) ◽  
pp. 483-504 ◽  
Author(s):  
Marius Ötting ◽  
Roland Langrock ◽  
Christian Deutscher
Keyword(s):  
Generalized Additive Model ◽  
Additive Model ◽  
Ground Truth ◽  
Warning Systems ◽  
Volume Data ◽  
Detection Systems ◽  
Multiple Data ◽  
Log Normal ◽  
Betting Odds

Recent years have seen several match-fixing scandals in soccer. In order to avoid match-fixing, existing literature and fraud detection systems primarily focus on analysing betting odds provided by bookmakers. In our work, we suggest to not only analyse odds but also total volume placed on bets, thereby making use of more of the information available. As a case study for our method, we consider the second division in Italian soccer, Serie B, since for this league it has effectively been proven that some matches were fixed, such that to some extent we can ground truth our approach. For the betting volume data, we use a flexible generalized additive model for location, scale and shape (GAMLSS), with log-normal response, to account for the various complex patterns present in the data. For the betting odds, we use a GAMLSS with bivariate Poisson response to model the number of goals scored by both teams, and to subsequently derive the corresponding odds. We then conduct outlier detection in order to flag suspicious matches. Our results indicate that monitoring both betting volumes and betting odds can lead to more reliable detection of suspicious matches.

scholarly journals Challenges in Quantifying Air‐Water Carbon Dioxide Flux Using Estuarine Water Quality Data: Case Study for Chesapeake Bay

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Maria Herrmann ◽  
Raymond G. Najjar ◽  
Fei Da ◽  
Jaclyn R. Friedman ◽  
Marjorie A. M. Friedrichs ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Chesapeake Bay ◽  
Carbon Dioxide Flux ◽  
Quality Data ◽  
Estuarine Water ◽  
Water Quality Data ◽  
Estuarine Water Quality

Assessing shallow landslide susceptibility by using the Generalized Additive Model: a case study

2018 ◽  
Vol 46 ◽  
pp. 115-121
Author(s):  
Carlotta Bartelletti ◽  
Yuri Galanti ◽  
Michele Barsanti ◽  
Roberto Giannecchini ◽  
Giacomo D'Amato Avanzi ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Shallow Landslide
Sign in / Sign up

Export Citation Format

Share Document