Full model comparison.
收藏Figshare2020-09-08 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Full_model_comparison_/12930569
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资源简介：
Δ ELPD is the difference in expected log predictive density (ELPD) between each model and the winning model. SE Δ approximates the standard error of the difference between each model and the winning model. ELPD and SE ELPD give each model’s expected log predictive density and their standard error. peff and SE peff estimates the effective number of parameters in each model and the standard error of this estimate.
创建时间：
2020-09-08
