Improving upon the effective sample size based on Godambe information for block likelihood inference
Author:
Funder
Science and Engineering Research Board
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s00180-023-01328-6.pdf
Reference17 articles.
1. Acosta J, Alegría A, Osorio F, Vallejos R (2021) Assessing the effective sample size for large spatial datasets: a block likelihood approach. Comput Stat Data Anal 162:107282
2. Acosta J, Vallejos R (2018) Effective sample size for spatial regression models. Electron J Stat 12:3147–3180
3. Bayley GV, Hammersley JM (1946) The “effective” number of independent observations in an autocorrelated times series. J R Stat Soc Suppl 8:184–197
4. Berger J, Bayarri MJ, Pericchi LR (2014) The effective sample size. Econom Rev 33:197–217
5. Bevilacqua M, Gaetan C (2015) Comparing composite likelihood methods based on pairs for spatial Gaussian random fields. Stat Comput 25:877–892
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