Results 121 to 130 of about 50,759 (165)
Generalized Multilevel Multisource Functional Regression With an Application to Alzheimer's Disease. [PDF]
Stat MedDu X, Yi G, Ren Y, Zhang Z, Mi H.
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Bayesian modeling of Escherichia coli contamination in household drinking water in Bangladesh: evidence from the Multiple Indicator Cluster Survey 2019. [PDF]
Int HealthHaq I +4 more
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A staged Bayesian framework for longitudinal prediction of adolescent depression using add health data. [PDF]
BMC Med Res MethodolRamezani N, Azugbene EA, Wilson JR.
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Assessing Unmeasured Confounding in Observational Research via Bayesian Semiparametric Modeling. [PDF]
Obs StudXu X, MacEachern SN, Lu B.
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Protocol for constructing multi-ancestry polygenic models using S4-Multi. [PDF]
STAR ProtocLai PH +4 more
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Statistics and Computing, 2008
We review adaptive Markov chain Monte Carlo algorithms (MCMC) as a mean to optimise their performance. Using simple toy examples we review their theoretical underpinnings, and in particular show why adaptive MCMC algorithms might fail when some fundamental properties are not satisfied.
Christophe Andrieu
exaly +5 more sources
We review adaptive Markov chain Monte Carlo algorithms (MCMC) as a mean to optimise their performance. Using simple toy examples we review their theoretical underpinnings, and in particular show why adaptive MCMC algorithms might fail when some fundamental properties are not satisfied.
Christophe Andrieu
exaly +5 more sources
MCMC and the fibonacci distribution
Communications in Statistics - Simulation and Computation, 2015ABSTRACTA method to create a Markov transition matrix for Markov chain Monte Carlo studies is presented and applied to the Fibonacci probability distribution.
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Statistics and Computing, 2006
We propose to combine two quite powerful ideas that have recently appeared in the Markov chain Monte Carlo literature: adaptive Metropolis samplers and delayed rejection. The ergodicity of the resulting non-Markovian sampler is proved, and the efficiency of the combination is demonstrated with various examples.
H. HAARIO +3 more
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We propose to combine two quite powerful ideas that have recently appeared in the Markov chain Monte Carlo literature: adaptive Metropolis samplers and delayed rejection. The ergodicity of the resulting non-Markovian sampler is proved, and the efficiency of the combination is demonstrated with various examples.
H. HAARIO +3 more
openaire +3 more sources
SPE EUROPEC/EAGE Annual Conference and Exhibition, 2010
Abstract The ensemble Kalman filter (EnKF) has recently become a popular history-matching tool largely because of its computational efficiency and ease of implementation. While EnKF has improved a previous history match obtained manually in several field cases, and often appears to give reasonable results for realistic synthetic history ...
Alexandre A. Emerick, Albert C. Reynolds
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Abstract The ensemble Kalman filter (EnKF) has recently become a popular history-matching tool largely because of its computational efficiency and ease of implementation. While EnKF has improved a previous history match obtained manually in several field cases, and often appears to give reasonable results for realistic synthetic history ...
Alexandre A. Emerick, Albert C. Reynolds
openaire +1 more source