biplots: Biplots

In myaseen208/bayesammi: Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model

Biplots

Description

biplots

Usage

## Default S3 method:
biplots(
  model,
  burnin = 0.3,
  thin = 0.2,
  pb = 0.05,
  plot_stable = TRUE,
  plot_unstable = TRUE,
  ncolors = 5
)

Arguments

model	Output from 'bayes_ammi()'. This should contain the results of the Bayesian AMMI model, including all sampled iterations.
burnin	Numeric. Percentage of iterations to discard as burn-in to avoid the effects of random initializations during sampling. For example, 'burnin = 0.1' removes the first 10% of iterations.
thin	Numeric. Proportion of sampled iterations to retain for analysis. For example, 'thin = 0.2' keeps 20% of the iterations, selecting 1 out of every 5 iterations.
pb	Numeric. Significance levels for the contours in the plot. Smaller values of 'pb' result in wider contours, while higher values create smaller, more specific contours.
plot_stable	Logical. If 'TRUE', stable instances are highlighted in the output plot.
plot_unstable	Logical. If 'TRUE', unstable instances are highlighted in the output plot.
ncolors	Integer. Specifies the number of distinct colors to use in the plot. Adjust this to control the visual differentiation of elements in the plot.

Value

A list with the following components:

plot

A plot displaying the contours and final biplot values.

contour_data

A 'data.frame' containing the data used to create the contours.

biplot_data

A 'data.frame' containing the data used to recreate the final biplot values.

Author(s)

1. Julian Garcia Abadillo Velasco ([e-mail])

2. Diego Jarquin ([e-mail])

References

Crossa, J., Perez-Elizalde, S., Jarquin, D., Cotes, J.M., Viele, K., Liu, G., and Cornelius, P.L. (2011) Bayesian Estimation of the Additive Main Effects and Multiplicative Interaction Model Crop Science, 51, 1458–1469. (doi: 10.2135/cropsci2010.06.0343)

Examples

## Not run: 
data(Maiz)

fm1 <-
  bayes_ammi(
    .data = Maiz,
    .y = y,
    .gen = entry,
    .env = site,
    .rep = rep,
    .nIter = 200
  )

library(ggplot2)

output_05 <- biplots(model = fm1, plot_stable = TRUE, plot_unstable = TRUE, pb = 0.05)
output_05

output_95 <- biplots(model = fm1, plot_stable = TRUE, plot_unstable = TRUE, pb = 0.95)
output_95

## End(Not run)

myaseen208/bayesammi documentation built on Nov. 28, 2024, 7:03 a.m.