中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 植物研究所
  3. 中国科学院植物研究所
  4. 植被与环境变化国家重点实验室
Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package

文献类型：期刊论文

作者Lai, Jiangshan1; Zou, Yi6; Zhang, Jinlong5; Peres-Neto, Pedro R.
刊名METHODS IN ECOLOGY AND EVOLUTION
出版日期2022
卷号13期号:4页码:782-788
ISSN号2041-210X
关键词averaging over orderings CCA commonality analysis constrained ordination db-RDA explained variation RDA relative importance
DOI10.1111/2041-210X.13800
文献子类Article
英文摘要Canonical analysis, a generalization of multiple regression to multiple-response variables, is widely used in ecology. Because these models often involve many parameters (one slope per response per predictor), they pose challenges to model interpretation. Among these challenges, we lack quantitative frameworks for estimating the overall importance of single predictors in multi-response regression models. Here we demonstrate that commonality analysis and hierarchical partitioning, widely used for both estimating predictor importance and improving the interpretation of single-response regression models, are related and complementary frameworks that can be expanded for the analysis of multiple-response models. In this application, we (a) demonstrate the mathematical links between commonality analysis, variation and hierarchical partitioning; (b) generalize these frameworks to allow the analysis of any number of predictor variables or groups of predictor variables as in the case of variation partitioning; and (c) introduce and demonstrate the implementation of these generalized frameworks in the R package rdacca.hp.
学科主题Ecology
电子版国际标准刊号2041-2096
出版地HOBOKEN
WOS关键词RELATIVE IMPORTANCE ; DOMINANCE ANALYSIS ; PREDICTORS
WOS研究方向Science Citation Index Expanded (SCI-EXPANDED) ; Social Science Citation Index (SSCI)
语种英语
出版者WILEY
WOS记录号WOS:000777994600003
资助机构National Science and Technology Basic Resources Survey Program of China [2019FY100204] ; Strategic Priority Research Program of the Chinese Academy of Sciences [XDA19050404] ; Canada Research Chair (CRC) program
源URL[http://ir.ibcas.ac.cn/handle/2S10CLM1/28666]  
专题植被与环境变化国家重点实验室
作者单位1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China
2.Peres-Neto, Pedro R.] Concordia Univ, Canada Res Chair Biodivers & Spatial Ecol, Montreal, PQ, Canada
3.Peres-Neto, Pedro R.] Concordia Univ, Dept Biol, Montreal, PQ, Canada
4.Kadoorie Farm & Bot Garden, Flora Conservat Dept, Hong Kong, Peoples R China
5.Xian Jiaotong Liverpool Univ, Dept Hlth & Environm Sci, Suzhou, Peoples R China
6.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Lai, Jiangshan,Zou, Yi,Zhang, Jinlong,et al. Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package[J]. METHODS IN ECOLOGY AND EVOLUTION,2022,13(4):782-788.
APA Lai, Jiangshan,Zou, Yi,Zhang, Jinlong,&Peres-Neto, Pedro R..(2022).Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.METHODS IN ECOLOGY AND EVOLUTION,13(4),782-788.
MLA Lai, Jiangshan,et al."Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package".METHODS IN ECOLOGY AND EVOLUTION 13.4(2022):782-788.

入库方式： OAI收割

来源：植物研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。