ggplot_discrimitiveness_vs_representativeness: Return a "discrimitiveness vs representativeness" ggplot...
In priviere/PPBstats: An R package to perform analysis found within PPB programmes

Description Usage Arguments Details Value Author(s) See Also

View source: R/ggplot_discrimitiveness_vs_representativeness.R

ggplot_discrimitiveness_vs_representativeness returns a "discrimitiveness vs representativeness" ggplot based on PCA object

1	ggplot_discrimitiveness_vs_representativeness(res.pca)

res.pca

output from biplot_data.check_model_GxE

It is a list of three elements. The two first elements where the plots are drawn under the same construction. A red circle indicates the position of the average location, which is defined by the average Dim1 and Dim2 scores across all locations. An arrow points this average 'virtual' location. A red line passes through the biplot origin and the average location (known as the Average-Tester Axis (ATA)).

discrimitiveness : assess discrimitiveness of each location. The score represents the discrimination : the higher the vector, the more discriminating the location.
representativeness : assess representativeness of each location. The score represents the representativeness : the higher the score, the less representative the location.
discrimitiveness_vs_representativeness : represent discrimitiveness versus representativeness. The location combining better score (i. e.discrimination and representativeness) are the ones that could be used to test germplasms as they are more representative of all the locations. This has to be done severals year to get robust results. The highest the score, the more disciminative and representative the location.

A ggplot object.

Pierre Riviere

plot.PPBstats plot.biplot_GxE

priviere/PPBstats documentation built on May 6, 2021, 1:20 a.m.