scholarly journals Outbreak‐Based Giardia Dose–Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis

Risk Analysis ◽  
2019 ◽  
Vol 40 (4) ◽  
pp. 705-722
Author(s):  
Tucker R. Burch
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Dose Response ◽  
Monte Carlo Analysis ◽  
Response Model ◽  
Bayesian Hierarchical

Harnessing the Theoretical Foundations of the Exponential and Beta-Poisson Dose-Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo

Risk Analysis ◽  
2013 ◽  
Vol 33 (9) ◽  
pp. 1677-1693 ◽  
Author(s):  
Philip J. Schmidt ◽  
Katarina D. M. Pintar ◽  
Aamir M. Fazil ◽  
Edward Topp
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Dose Response ◽  
Parameter Uncertainty ◽  
Response Models ◽  
Theoretical Foundations

scholarly journals Application of Markov chain Monte Carlo analysis to biomathematical modeling of respirable dust in US and UK coal miners

2013 ◽  
Vol 66 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Lisa M. Sweeney ◽  
Ann Parker ◽  
Lynne T. Haber ◽  
C. Lang Tran ◽  
Eileen D. Kuempel
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Monte Carlo Analysis ◽  
Respirable Dust ◽  
Coal Miners ◽  
Biomathematical Modeling

scholarly journals The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte Carlo analysis of gravitational-wave signals

2010 ◽  
Vol 27 (11) ◽  
pp. 114009 ◽  
Author(s):  
V Raymond ◽  
M V van der Sluys ◽  
I Mandel ◽  
V Kalogera ◽  
C Röver ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Gravitational Wave ◽  
Monte Carlo Analysis ◽  
Detector Noise

scholarly journals Potential sources of red snapper (Lutjanus campechanus) recruits estimated with Markov Chain Monte Carlo analysis of otolith chemical signatures

2016 ◽  
Vol 67 (7) ◽  
pp. 992 ◽  
Author(s):  
Beverly K. Barnett ◽  
William F. Patterson ◽  
Todd Kellison ◽  
Steven B. Garner ◽  
Alan M. Shiller
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Chemical Constituents ◽  
Monte Carlo Analysis ◽  
Red Snapper ◽  
Lutjanus Campechanus ◽  
Age Classes ◽  
Elemental Ratios ◽  
Chemical Signatures

Otolith chemical signatures were used to estimate the number of likely nursery sources that contributed recruits to a suite of red snapper (Lutjanus campechanus) year-classes sampled in 2012 in US Atlantic Ocean waters from southern Florida (28°N) to North Carolina (34°N). Otoliths from subadult and adult fish (n=139; ages 2–5 years) were cored and their chemical constituents analysed for δ13C, δ18O, as well as the elemental ratios of Ba:Ca, Mg:Ca, Mn:Ca and Sr:Ca. Results from multiple linear regression analyses indicated that there was significant latitudinal variation for δ13C, Ba:Ca, Mg:Ca and Mn:Ca. Therefore, these variables were used to parameterise Markov Chain Monte Carlo (MCMC) models computed to estimate the most likely number of nursery sources to each age class. Results from MCMC models indicated that between two and seven nursery sources were equally plausible among the four age classes examined, but the likely number of nursery sources declined for fish aged 4 and 5 years because of apparent mixing between more northern and more southern signatures. Overall, there is evidence to reject the null hypothesis that a single nursery source contributed recruits among the age classes examined, but increased sample size from a broader geographic range may be required to refine estimates of the likely number of nursery sources.

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