Improved Sampling‐Importance Resampling and Reduced Bias Importance Sampling

DOI10.1111/1467-9469.00360zbMath1055.65019OpenAlexW2091933470MaRDI QIDQ4828215

Øivind Skare, Lars Holden, Bølviken, Erik

Publication date: 24 November 2004

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9469.00360

zbMATH Keywords

convergenceMarkov chain Monte Carlo methodMetropolis-Hastings algorithmsampling-importance resamplingtotal variance norm

Mathematics Subject Classification ID

Related Items (13)

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Cites Work

• Unnamed Item
• Unnamed Item
• Option pricing under model and parameter uncertainty using predictive densities
• Geometric convergence of the Metropolis-Hastings simulation algorithm
• Hyperparameter estimation in forecast models.
• Rates of convergence of the Hastings and Metropolis algorithms
• Sequential Monte Carlo Methods in Practice
• Prediction of Reservoir Variables Based on Seismic Data and Well Observations
• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

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