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Practical Bayesian Modeling and Inference for Massive Spatial Datasets On Modest Computing Environments
With continued advances in Geographic Information Systems and related computational technologies, statisticians are often required to analyze very large spatial datasets. This has generated substantial interest over the last decade, already too vast to be summarized here, in scalable methodologies f...
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| 出版年: | Stat Anal Data Min |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8048149/ https://ncbi.nlm.nih.gov/pubmed/33868538 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sam.11413 |
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