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141

Bayesian inference for the Brown-Resnick process, with an application to extreme low temperatures

by Thibaud, Emeric, Aalto, Juha, Cooley, Daniel S., Davison, Anthony C., Heikkinen, Juha
Published 2015
“... in a Markov chain Monte Carlo algorithm. We use these approaches to construct a Bayesian hierarchical...”

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142

Estimations of Evapotranspiration and Water Balance with Uncertainty over the Yukon River Basin

by Wenping Yuan, Shuguang Liu, Shunlin Liang, Zhengxi Tan, Heping Liu, Claudia Young
“... Springer Science+Business Media B.V. 2012 Evapotranspiration, Bayesian approach, Markov chain Monte Carlo...”

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143

Rates of evolution in ancient DNA from Adelie penguins

by Lambert, David Martin, Ritchie, Peter A., Millar, Craig D., Holland, B., Drummond, A.J., Baroni, Carlo
Published in Science (2002)
“... of evolution of the hypervariable region I using a Markov chain Monte Carlo integration and a least-squares...”

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144

Recovering ‘lost’ information in the presence of noise: application to rodent–predator dynamics.

by Smelyanskiy, V. N., Luchinsky, D. G., Millonas, M. M., McClintock, P. V. E.
Published in New Journal of Physics (2009)
“...-spaces. The performance of the method is compared with that of the conventional Markov chain Monte Carlo...”

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145

Bayesian inference of recent migration rates using multilocus genotypes.

by Wilson, Gregory A, Rannala, Bruce
Published 2003
“... in a computer program that relies on Markov chain Monte Carlo techniques to carry out the estimation...”

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146

Bayesian modelling of catch in a north‐west Atlantic fishery

by Carmen Fernández, Eduardo Ley, Mark F. J. Steel
Published in Journal of the Royal Statistical Society: Series C (Applied Statistics)
“... model. Inference is based on Bayesian model averaging, using a Markov chain Monte Carlo approach...”

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147

Rates of Evolution in Ancient DNA from Adélie Penguins

by University, Griffith
Published 2014
“... of evolution of the hypervariable region I using a Markov chain Monte Carlo integration and a least-squares...”

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148

Modeling Interdependent Animal Movement in Continuous Time

by Niu, Mu, Blackwell, Paul G., Skarin, Anna
Published in Biometrics (2016)
“... parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings...”

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149

A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

by Nakano, Shin'Ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
Published in Nonlinear Processes in Geophysics (2016)
“... the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC...”

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150

A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

by Nakano, Shin'ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
Published in Nonlinear Processes in Geophysics (2016)
“... the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC...”

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151

A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

by Nakano, Shin'Ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
Published in Nonlinear Processes in Geophysics (2016)
“... the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC...”

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152

A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

by Nakano, Shin'Ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
Published in Nonlinear Processes in Geophysics (2016)
“... the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC...”

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153

A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

by Nakano, Shin'Ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
Published in Nonlinear Processes in Geophysics (2016)
“... the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC...”

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154

Bayesian analysis of rapid climate change during the last glacial using Greenland δ18O data

by Peavoy, D., Franzke, C.
Published in Climate of the Past (2018)
“... timescales. A Markov Chain Monte Carlo method is presented to infer the number of states in a latent variable...”

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155

Statistical modeling of fishing activities in the north atlantic

by Carmen Fernández, Eduardo Ley, Mark F. J. Steel
Published 1997
“... inference will be based on Bayesian model averaging, using a Markov Chain Monte Carlo Model Composition (MC...”

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156

Climate and solar signals in property damage losses from hurricanes affecting the United States

by Thomas Jagger, James Elsner, R. Burch
“... Markov chain Monte Carlo procedure is used to generate posterior samples from the models. Results...”

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157

Multi-star Turbulence Monitor: A new technique to measure optical turbulence profiles

by Hickson, Paul, Ma, Bin, Shang, Zhaohui, Xue, Suijian
Published 2019
“.... These are compared with theoretical predictions of simple turbulence models by means of a Markov-Chain Monte-Carlo...”

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158

Bayesian hierarchical model for variations in earthquake peak ground acceleration within small‐aperture arrays

by Sahar Rahpeyma, Benedikt Halldorsson, Birgir Hrafnkelsson, Sigurjón Jónsson
Published in Environmetrics
“... based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance...”

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159

Bayesian hierarchical model for variations in earthquake peak ground acceleration within smallâ€ aperture arrays

by Sahar Rahpeyma, Benedikt Halldorsson, Birgir Hrafnkelsson, Sigurjón Jónsson
Published in Environmetrics
“.... An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed...”

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160

Gaussian process convolutions for Bayesian spatial classification

by Best, John K.
Published 2016
“... generated using a process convolution. A grid of knots (whose values were sampled using Markov Chain Monte...”

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