Best-ranked logistic regression models with Evidence Ratio ≤ 2.5.

Figshare2018-02-08 更新2026-04-29 收录

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Best-ranked logistic regression models with Evidence Ratio ≤ 2.5.

创建时间：

2018-02-08

Binomial logistic regression model selection results of proportional C 4 richness for Poaceae, Cyperaceae, Chenopodiaceae, and Euphorbiaceae.

C3/C4植物生态

逻辑回归模型选择

Binomial logistic regression model selection results of proportional C4 richness for Poaceae, Cyperaceae, Chenopodiaceae, and Euphorbiaceae.

NIAID Data Ecosystem30

Model type, predictor variables, Deviance Information Criteria (DIC), ΔDIC, and DIC weights () for the candidate set of logistic regression models relating misidentification of sex with personal background information.

逻辑回归模型选择

性别误识别预测

DIC is a measure of model fit, ΔDIC measures the relative difference between the best model (ΔDIC = 0) and all subsequent models in the model set, and is the relative likelihood of a model given the

NIAID Data Ecosystem20

Model-selection analysis for logistic regression modeling of swine farm distribution in the conterminous U.S.

物种空间分布建模

逻辑回归模型选择

a Covariates with prefix d are measured as distance to the environmental or anthropogenic feature. Results are shown for models with AICΔi ≤ 2.0 and all these models were used to develop model-average

NIAID Data Ecosystem20

Best fitting model structures considered for logistic regression predictive model with associated Akaike Information Criterion (AICc) scores (corrected for small sample sizes).

逻辑回归模型选择

AICc准则

Best fitting model structures considered for logistic regression predictive model with associated Akaike Information Criterion (AICc) scores (corrected for small sample sizes).

NIAID Data Ecosystem30

Model selection values of the candidate models of binary logistic regression.

逻辑回归模型选择

分类模型评估

Model selection values of the candidate models of binary logistic regression.

NIAID Data Ecosystem20