A Monte Carlo approach to estimate the uncertainty in soil CO 2 emissions caused by spatial and sample size variability

Ecology and Evolution ◽

10.1002/ece3.1729 ◽

2015 ◽

Vol 5 (19) ◽

pp. 4480-4491 ◽

Author(s):

Wei‐Yu Shi ◽

Li‐Jun Su ◽

Yi Song ◽

Ming‐Guo Ma ◽

Sheng Du

Keyword(s):

Monte Carlo ◽

Sample Size ◽

Monte Carlo Approach ◽

Size Variability

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Sample Size Estimation for Pilot Animal Experiments by Using a Markov Chain Monte Carlo Approach

Alternatives to Laboratory Animals ◽

10.1177/026119291704500201 ◽

2017 ◽

Vol 45 (2) ◽

pp. 83-90 ◽

Author(s):

Andreas Allgoewer ◽

Benjamin Mayer

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Sample Size ◽

Animal Experiments ◽

Sample Size Estimation ◽

Size Estimation ◽

Monte Carlo Approach

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Review of Sample Size for Structural Equation Models in Second Language Testing and Learning Research: A Monte Carlo Approach

International Journal of Testing ◽

10.1080/15305058.2013.806925 ◽

2013 ◽

Vol 13 (4) ◽

pp. 329-353 ◽

Author(s):

Yo In’nami ◽

Rie Koizumi

Keyword(s):

Monte Carlo ◽

Second Language ◽

Sample Size ◽

Structural Equation ◽

Structural Equation Models ◽

Language Testing ◽

Monte Carlo Approach ◽

Learning Research

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A two-stage Monte Carlo approach to the expression of uncertainty with non-linear measurement equation and small sample size

10.1088/0026-1394/43/1/005 ◽

2005 ◽

Vol 43 (1) ◽

pp. 34-41 ◽

Author(s):

Stephen V Crowder ◽

Robert D Moyer

Keyword(s):

Monte Carlo ◽

Sample Size ◽

Small Sample Size ◽

Linear Measurement ◽

Small Sample ◽

Two Stage ◽

Measurement Equation ◽

Monte Carlo Approach ◽

Expression Of Uncertainty

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Derivation of minimum best sample size from microarray data sets: A Monte Carlo approach

2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

10.1109/cibcb.2011.5948461 ◽

2011 ◽

Author(s):

Chengpeng Bi ◽

Mara Becker ◽

Steve Leeder

Keyword(s):

Monte Carlo ◽

Sample Size ◽

Microarray Data ◽

Data Sets ◽

Monte Carlo Approach

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Sample Size and Power Estimates for a Confirmatory Factor Analytic Model in Exercise and Sport: A Monte Carlo Approach

Research Quarterly for Exercise and Sport ◽

10.5641/027013611x13275191443621 ◽

2011 ◽

Vol 82 (3) ◽

Author(s):

Nicholas Myers

Keyword(s):

Monte Carlo ◽

Sample Size ◽

Analytic Model ◽

Monte Carlo Approach ◽

Factor Analytic Model ◽

Factor Analytic ◽

Confirmatory Factor

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Sample size in multilevel structural equation modeling – the Monte Carlo approach

Econometrics ◽

10.15611/eada.2019.4.05 ◽

2019 ◽

Vol 23 (4) ◽

pp. 63-79

Author(s):

Adam Sagan

Keyword(s):

Monte Carlo ◽

Structural Equation Modeling ◽

Sample Size ◽

Structural Equation ◽

Multilevel Structural Equation Modeling ◽

Equation Modeling ◽

Monte Carlo Approach ◽

Multilevel Structural Equation

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Wigner-Boltzmann Monte Carlo approach to nanodevice simulation: from quantum to semiclassical transport

Journal of Computational Electronics ◽

10.1007/s10825-009-0281-3 ◽

2009 ◽

Vol 8 (3-4) ◽

pp. 324-335 ◽

Author(s):

Damien Querlioz ◽

Huu-Nha Nguyen ◽

Jérôme Saint-Martin ◽

Arnaud Bournel ◽

Sylvie Galdin-Retailleau ◽

...

Keyword(s):

Monte Carlo ◽

Monte Carlo Approach ◽

Semiclassical Transport

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Relaxation dynamics in small clusters: A modified Monte Carlo approach

Journal of Computational Physics ◽

10.1016/j.jcp.2007.11.007 ◽

2008 ◽

Vol 227 (4) ◽

pp. 2666-2673 ◽

Author(s):

Barnana Pal

Keyword(s):

Monte Carlo ◽

Relaxation Dynamics ◽

Monte Carlo Approach ◽

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The Role of Sample Size in Testing a Hypothesis in Complex Cross-Sectional Studies: A Monte Carlo Simulation Study

Studies in Economics and Econometrics ◽

10.1080/10800379.2008.12106450 ◽

2008 ◽

Vol 32 (2) ◽

pp. 63-68

Author(s):

P A E Serumaga-Zake ◽

R Arnab

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Sample Size ◽

Simulation Study ◽

Cross Sectional ◽

Monte Carlo Simulation Study ◽

Complex Cross ◽

Cross Sectional Studies

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Uncertainty study on atmospheric dispersion simulations using meteorological ensembles with a Monte Carlo approach, applied to the Fukushima nuclear accident

Atmospheric Environment X ◽

10.1016/j.aeaoa.2021.100112 ◽

2021 ◽

pp. 100112

Author(s):

Ngoc Bao Tran LE ◽

Irène Korsakissok ◽

Vivien Mallet ◽

Raphaël Périllat ◽

Anne Mathieu

Keyword(s):

Monte Carlo ◽

Atmospheric Dispersion ◽

Nuclear Accident ◽

Fukushima Nuclear Accident ◽

Monte Carlo Approach

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