Skip to main navigation
Skip to search
Skip to main content
University of St Andrews Research Portal Home
Help & FAQ
Home
Profiles
Research output
Datasets
Research units
Projects
Activities
Impacts
Prizes
Press/Media
Student theses
Search by expertise, name or affiliation
An Eigenvalue test for spatial principal component analysis
V. Montano
*
, T. Jombart
*
Corresponding author for this work
School of Biology
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'An Eigenvalue test for spatial principal component analysis'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Local Test
100%
Eigenvalue Test
100%
Principal Component Analysis
100%
Statistical Power
66%
Parametric Test
33%
Spatial Distribution
33%
Biochemistry, Genetics and Molecular Biology
Principal Component Analysis
100%
Genetic Divergence
50%
Genetics
50%
Genetic Model
50%
Genetic Variation
50%
Population Genetics
50%
Earth and Planetary Sciences
Principal Component Analysis
100%
Population Genetics
50%
Genetic Variation
50%
Spatial Distribution
50%
Neuroscience
Population Genetics
100%
Genetic Variation
100%
Economics, Econometrics and Finance
Principal Components
100%