2017
DOI: 10.1201/b21874
|View full text |Cite
|
Sign up to set email alerts
|

Exploratory Multivariate Analysis by Example Using R

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
434
0
24

Year Published

2017
2017
2024
2024

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 551 publications
(542 citation statements)
references
References 2 publications
1
434
0
24
Order By: Relevance
“…We examined genetic population structure with STRUC-TURE version 2.3.4 (Pritchard et al 2000). To further test for genetic structure, we employed principal component analysis (PCA), with FactoMineR (Husson et al 2010) in R. STRUC-TURE and PCA were performed on both the GBS and RNAseq datasets. As our sampling design did not include the purported cytotype contact zone (shaded area in Fig.…”
Section: Demographic Analysesmentioning
confidence: 99%
“…We examined genetic population structure with STRUC-TURE version 2.3.4 (Pritchard et al 2000). To further test for genetic structure, we employed principal component analysis (PCA), with FactoMineR (Husson et al 2010) in R. STRUC-TURE and PCA were performed on both the GBS and RNAseq datasets. As our sampling design did not include the purported cytotype contact zone (shaded area in Fig.…”
Section: Demographic Analysesmentioning
confidence: 99%
“…To assess how traits covaried, we performed a principal component analysis (PCA) on the fourteen quantitative traits using the R package 'FactoMineR' (Husson et al 2010). For each trait, we scaled the data to the unit variance.…”
Section: Trait Analysesmentioning
confidence: 99%
“…62 ] (v.test criterion) also gives an indication of whether the mean of the cluster for that variable is larger (positive sign) or smaller (negative sign) than the overall mean in the dataset. 70 Only significant variables in clusters were considered. Finally, the supplementary categories (i.e.…”
Section: Methodsmentioning
confidence: 99%