Intensity models.

Figshare2021-10-05 更新2026-04-28 收录

血吸虫感染强度建模

多模型推断

数据链接：

https://figshare.com/articles/dataset/Intensity_models_/16745595 数据链接链接失效反馈

官方服务：

资源简介：

Full set of candidate models used for multi-model inference of the relative contributions of exposure, hazard, and vulnerability to S. haematobium infection intensity. (XLSX)

创建时间：

2021-10-05

Model-averaged coefficients and their unconditional 95% confidence intervals.

多模型推断

参数估计

Model-averaged coefficients were estimated by multimodel inference following model selection (see Table 1) and computed with standardized explanatory variables (zero mean and unit variance). Parameter

NIAID Data Ecosystem50

Importance value (Σwi) of each independent variables for each model selection group.

模型变量重要性

多模型推断

**Variables that were part of the models with ΔAICc wi*variables that were part of the models with ΔAICc wiImportance value (Σwi) of each independent variables for each model selection group.

Figshare2015-12-03 更新30

The 5 best-fitting linear models for each dependent variable.

统计模型选择

多模型推断

AICc is Akaike’s information criterion corrected for small sample size, δAICc is the difference in AICc values between the best model and a given model, ω is Akaike weight reflecting the probability t

Figshare2015-12-02 更新20

Combined analysis: models with ΔAICc<2 in the 128-model set used for inference (see Table S1 for the complete model set).

模型评估

多模型推断

AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc relative to the best-performing model; Likelihood: likelihood of the model, given the data; wi: Akaike we

Figshare2015-12-02 更新30

Model-averaging results for all-taxa, birds-only, and bats-only top model sets.

物种分布建模

多模型推断

Included are standardized coefficient estimates (Estimate), unconditional standard errors (SE), and 95% confidence intervals (CI) for each model set. Shaded rows represent variables with confidence in

NIAID Data Ecosystem30

Intensity models.

资源简介：

相关数据集