首页|g1mm.hp包对零膨胀广义线性混合模型与多元回归的扩展

g1mm.hp包对零膨胀广义线性混合模型与多元回归的扩展

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glmm.hp是一个专为评估广义线性混合模型(GLMMs)中共线预测变量的相对重要性而开发的R包.自从其于2022年1月发布以来,已迅速在生态学界获得认可和流行.然而,先前的glmm.hp包仅限于处理仅来源于Ime4和nlme包的GLMMs.最新的glmm.hp包增加了新功能.首先,它整合了从glmmTMB包获得的结果,使其能够有效地处理零膨胀广义线性混合模型.此外,最新的glmm.hp包添加了基于原始R2和校正R2的普通多元回归的共性分析和层次分割的功能.本文将展示这些新功能,更方便广大的研究人员使用.
Extension of the glmm.hp package to zero-inflated generalized linear mixed models and multiple regression
glmm.hp is an R package designed to evaluate the relative importance of collinear predictors within generalized linear mixed models(GLMMs).Since its initial release in January 2022,it has been rapidly gained recognition and popularity among ecologists.However,the previous glmm.hp package was limited to work GLMMs derived exclusively from the Ime4 and nlme packages.The latest glmm.hp package has extended its functions.It has integrated results obtained from the glmmTMB package,thus enabling it to handle zero-inflated generalized linear mixed models(ZIGLMMs)effectively.Furthermore,it has introduced the new functionalities of commonality analysis and hierarchical partitioning for multiple linear regression models by considering both unadjusted R2 and adjusted R2.This paper will serve as a demonstration for the applications of these new functionalities,making them more accessible to users.

commonality analysisGLMMshierarchical partitioningmarginal R2multiple regressionrelative importancevariance partitioningzero-Inflated model

Jiangshan Lai、Weijie Zhu、Dongfang Cui、Lingfeng Mao

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College of Ecology and Environment,Nanjing Forestry University,Nanjing 210037,China

Research Center of Quantitative Ecology,Nanjing Forestry University,Nanjing 210037,China

共性分析 广义混合效应模型 层次分割 边际R2 多元回归 相对重要性 方差分解 零膨胀模型

国家自然科学基金Metasequoia funding of Nanjing Forestry University.Conflict of interest statement

32271551

2023

10.1093/jpe/rtad038

植物生态学报(英文版)

植物生态学报(英文版)

CSCD
ISSN：1752-9921
年,卷(期)：2023.(6)
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