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Appendix B. Estimating the likelihood of each data set given each model.

NIAID Data Ecosystem2026-03-09 收录

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https://figshare.com/articles/dataset/Appendix_B_Estimating_the_likelihood_of_each_data_set_given_each_model_/3514490 数据链接链接失效反馈

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Estimating the likelihood of each data set given each model.

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创建时间：

2016-08-04

HPV抗体建模

生态统计模型

See Table 1 for explanation of scenarios. : posterior mean deviance. : deviance of posterior means.: effective dimension as [26]. DIC(1): deviance information criterion as . : effective dimension as

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Analysis of variance results for change in dial readings over the course of science messages for the TNet and TSLR statistical models.

科学传播效果评估

生态统计模型

Analysis of variance results for change in dial readings over the course of science messages for the TNet and TSLR statistical models.

Figshare2019-12-09 更新20

Results of applying the multiple range test to mean absolute error.

生态统计模型

多重范围检验

The F-value corresponds to the ANOVA, which checks the equality of all the means. Also indicated is mean absolute error (in ascending order) for each model. The last column indicates the predictive va

Figshare2018-07-10 更新20

Maximum likelihood parameters of the best model

天体生物学模型

最大似然估计

File with model specification and maximum likelihood parameters of the model with highest likelihood among all models tested ("speciation from a hybrid population at Python Island").

DataONE2016-09-08 更新60

Model-averaging results for fecundity linear models.

种群繁殖力建模

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Model-averaged beta coefficients (β), bootstrapped unconditional standard errors (SE), 95% confidence interval lower and upper limits (LCL and UCL), and summed AIC weights (ω+) of parameters for model

Figshare2015-12-03 更新20

Appendix B. Estimating the likelihood of each data set given each model.

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