Objective Bayes Inference and MCMC

2021 ◽  
pp. 243-274
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Simo Kitanovski ◽  
Gibran Horemheb-Rubio ◽  
Ortwin Adams ◽  
Barbara Gärtner ◽  
Thomas Lengauer ◽  
...  

Abstract Background Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses. Methods We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany. With a probabilistic model for Bayes inference we quantified prevalence changes of the different viruses between months in the pre-pandemic period 2010-2019 and the corresponding months in 2020, the year of the pandemic with noninvasive measures of various degrees of stringency. Results We discovered remarkable reductions δ in rhinovirus (RV) prevalence by about 25% (95% highest density interval (HDI) [−0.35,−0.15]) in the months after the measures against SARS-CoV-2 were introduced in Germany. In the months after the measures began to ease, RV prevalence increased to low pre-pandemic levels, e.g. in August 2020 δ=−0.14 (95% HDI [−0.28,0.12]). Conclusions RV prevalence is negatively correlated with the stringency of anti-SARS-CoV-2 measures with only a short time delay. This result suggests that RV prevalence could possibly be an indicator for the efficiency for these measures. As RV is ubiquitous at higher prevalence than SARS-CoV-2 or other emerging respiratory viruses, it could reflect the efficacy of noninvasive measures better than such emerging viruses themselves with their unevenly spreading clusters.


Biometrika ◽  
2016 ◽  
Vol 103 (1) ◽  
pp. 35-47 ◽  
Author(s):  
Tsuyoshi Kunihama ◽  
David B. Dunson

2015 ◽  
Vol 2015 ◽  
pp. 1-5
Author(s):  
Naiyi Li ◽  
Yuan Li ◽  
Yongming Li ◽  
Yang Liu

This research is based on ranked set sampling. Through the analysis and proof, the empirical Bayes test rule and asymptotical property for the parameter of power distribution are obtained.


Author(s):  
Hau-Tieng Wu ◽  
Tze Leung Lai ◽  
Gabriel G. Haddad ◽  
Alysson Muotri

Herein we describe new frontiers in mathematical modeling and statistical analysis of oscillatory biomedical signals, motivated by our recent studies of network formation in the human brain during the early stages of life and studies forty years ago on cardiorespiratory patterns during sleep in infants and animal models. The frontiers involve new nonlinear-type time–frequency analysis of signals with multiple oscillatory components, and efficient particle filters for joint state and parameter estimators together with uncertainty quantification in hidden Markov models and empirical Bayes inference.


1985 ◽  
Vol R-34 (4) ◽  
pp. 377-381 ◽  
Author(s):  
C. A. Clarotti ◽  
G. Koch ◽  
F. Spizzichino
Keyword(s):  

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