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Everything about Biplot
Type of exploratory graph used in statistics
Biplots are a type of exploratory graph used in statistics, a generalization of the simple two-variable scatterplot. A biplot overlays a score plot with a loading plot. A biplot allows information on both samples and variables of a data matrix to be displayed graphically. Samples are displayed as points while variables are displayed either as vectors, linear axes or nonlinear trajectories. In the case of categorical variables, category level points may be used to represent the levels of a categorical variable. A generalised biplot displays information on both continuous and categorical variables. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: BiplotA 5-minute orientation
- Skim a recent paper: Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analysesInfluential work since 2022
- Pick up a classic book: GGE biplot analysisThe most-reprinted book on the subject
- Read the landmark paper: The biplot graphic display of matrices with application to principal component analysisCited 2,320 times
- Go sideways: Correspondence analysisA closely related topic
- Go sideways: Plot (graphics)A closely related topic
📖 Definitions
Noun A kind of statistical graph, a generalization of the simple two-variable scatter plot, allowing information on both samples and variables of a data matrix to be displayed graphically.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
The biplot graphic display of matrices with application to principal component analysis
Cultivar Evaluation and Mega‐Environment Investigation Based on the GGE Biplot
Biplot analysis of multi-environment trial data: Principles and applications
GGE Biplot vs. AMMI Analysis of Genotype‐by‐Environment Data
Biplot Analysis of Test Sites and Trait Relations of Soybean in Ontario
Biplot Analysis of Genotype × Environment Interaction: Proceed with Caution
An Integrated Biplot Analysis System for Displaying, Interpreting, and Exploring Genotype × Environment Interaction
A heritability-adjusted GGE biplot for test environment evaluation
🆕 Influential since 2022
Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses
Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI
AMMI and GGE biplot analyses of Bambara groundnut [Vigna subterranea (L.) Verdc.] for agronomic performances under three environmental conditions
Graphical analysis of multi-environmental trials for wheat grain yield based on GGE-biplot analysis under diverse sowing dates
Evaluation of Grain Yield Stability in Some Selected Wheat Genotypes Using AMMI and GGE Biplot Methods
📚 Books worth reading
GGE biplot analysisWeikai Yan, Manjit S. Kang · 2002- 📕Understanding BiplotsSugnet Gardner Lubbe, John C. Gower · 2010
BiplotsJ. C. Gower · 1995
Understanding biplotsJohn Gower · 2008- 📕Modern Quantification TheoryShizuhiko Nishisato, Rosaria Lombardo · 2021
Modern data analysisAndrew F. Siegel · 1982
Understanding biplotsJohn Gower · 2010
Biplots in practiceMichael J. Greenacre · 2010
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Scatter plot A scatter plot, also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram, is a type of plot or mathematical diagram using…
- Principal component analysis Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data…
- Covariance matrix In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance…
- Multiple correspondence analysis In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying…
- CUR matrix approximation A CUR matrix approximation is a set of three matrices C, U and R that, when multiplied together, closely approximate a given matrix. A CUR approximation…