[Stable]

This function computes the WAASY or WAASBY indexes (Olivoto et al., 2019) considering different scenarios of weights for stability and mean performance.

After fitting a model with the functions waas() or waasb() it is possible to compute the superiority indexes WAASY or WAASBY in different scenarios of weights for stability and mean performance. The number of scenarios is defined by the arguments increment. By default, twenty-one different scenarios are computed. In this case, the the superiority index is computed considering the following weights: stability (waasb or waas) = 100; mean performance = 0. In other words, only stability is considered for genotype ranking. In the next iteration, the weights becomes 95/5 (since increment = 5). In the third scenario, the weights become 90/10, and so on up to these weights become 0/100. In the last iteration, the genotype ranking for WAASY or WAASBY matches perfectly with the ranks of the response variable.

wsmp(
  model,
  mresp = 100,
  increment = 5,
  saveWAASY = 50,
  prob = 0.05,
  progbar = TRUE
)

Arguments

model

Should be an object of class waas or waasb.

mresp

A numeric value that will be the new maximum value after rescaling. By default, the variable in resp is rescaled so that the original maximum and minimum values are 100 and 0, respectively. Let us consider that for a specific trait, say, lodging incidence, lower values are better. In this case, you should use mresp = 0 to rescale the response variable so that the lowest values will become 100 and the highest values 0.

increment

The increment in the weight ratio for stability and mean performance. Se the Details section for more information.

saveWAASY

Automatically save the WAASY values when the weight for stability is saveWAASY. Default is 50. Please, note that saveWAASY

prob

The p-value for considering an interaction principal component axis significant. must be multiple of increment. If this assumption is not valid, an error will be occur.

progbar

A logical argument to define if a progress bar is shown. Default is TRUE.

Value

An object of class wsmp with the following items for each variable:

  • scenarios A list with the model for all computed scenarios.

  • WAASY The values of the WAASY estimated when the weight for the stability in the loop match with argument saveWAASY.

  • hetdata, hetcomb The data used to produce the heatmaps.

  • Ranks All the values of WAASY estimated in the different scenarios of WAAS/GY weighting ratio.

References

Olivoto, T., A.D.C. L\'ucio, J.A.G. da silva, V.S. Marchioro, V.Q. de Souza, and E. Jost. 2019. Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agron. J. doi: 10.2134/agronj2019.03.0220

See also

Author

Tiago Olivoto tiagoolivoto@gmail.com

Examples

# \donttest{ library(metan) model <- waasb(data_ge2, env = ENV, gen = GEN, rep = REP, resp = PH)
#> Evaluating trait PH |============================================| 100% 00:00:00
#> Method: REML/BLUP
#> Random effects: GEN, GEN:ENV
#> Fixed effects: ENV, REP(ENV)
#> Denominador DF: Satterthwaite's method
#> --------------------------------------------------------------------------- #> P-values for Likelihood Ratio Test of the analyzed traits #> --------------------------------------------------------------------------- #> model PH #> COMPLETE NA #> GEN 9.39e-01 #> GEN:ENV 1.09e-13 #> --------------------------------------------------------------------------- #> All variables with significant (p < 0.05) genotype-vs-environment interaction
scenarios <- wsmp(model)
#> Ranks considering 0 for GY and 100 for WAASB | | 2% 00:00:00 Ranks considering 0 for GY and 100 for WAASB |= | 3% 00:00:00 Ranks considering 0 for GY and 100 for WAASB |= | 5% 00:00:00 Ranks considering 5 for GY and 95 for WAASB |= | 6% 00:00:00 Ranks considering 5 for GY and 95 for WAASB |== | 8% 00:00:00 Ranks considering 5 for GY and 95 for WAASB |== | 10% 00:00:00 Ranks considering 10 for GY and 90 for WAASB |== | 11% 00:00:00 Ranks considering 10 for GY and 90 for WAASB |== | 13% 00:00:00 Ranks considering 10 for GY and 90 for WAASB |=== | 14% 00:00:00 Ranks considering 15 for GY and 85 for WAASB |=== | 16% 00:00:00 Ranks considering 15 for GY and 85 for WAASB |=== | 17% 00:00:00 Ranks considering 15 for GY and 85 for WAASB |==== | 19% 00:00:00 Ranks considering 20 for GY and 80 for WAASB |==== | 21% 00:00:00 Ranks considering 20 for GY and 80 for WAASB |==== | 22% 00:00:00 Ranks considering 20 for GY and 80 for WAASB |===== | 24% 00:00:00 Ranks considering 25 for GY and 75 for WAASB |===== | 25% 00:00:00 Ranks considering 25 for GY and 75 for WAASB |===== | 27% 00:00:00 Ranks considering 25 for GY and 75 for WAASB |===== | 29% 00:00:00 Ranks considering 30 for GY and 70 for WAASB |====== | 30% 00:00:00 Ranks considering 30 for GY and 70 for WAASB |====== | 32% 00:00:00 Ranks considering 30 for GY and 70 for WAASB |====== | 33% 00:00:00 Ranks considering 35 for GY and 65 for WAASB |======= | 35% 00:00:00 Ranks considering 35 for GY and 65 for WAASB |======= | 37% 00:00:00 Ranks considering 35 for GY and 65 for WAASB |======= | 38% 00:00:00 Ranks considering 40 for GY and 60 for WAASB |======== | 40% 00:00:00 Ranks considering 40 for GY and 60 for WAASB |======== | 41% 00:00:00 Ranks considering 40 for GY and 60 for WAASB |======== | 43% 00:00:00 Ranks considering 45 for GY and 55 for WAASB |======== | 44% 00:00:00 Ranks considering 45 for GY and 55 for WAASB |========= | 46% 00:00:00 Ranks considering 45 for GY and 55 for WAASB |========= | 48% 00:00:00 Ranks considering 50 for GY and 50 for WAASB |========= | 49% 00:00:00 Ranks considering 50 for GY and 50 for WAASB |========== | 51% 00:00:00 Ranks considering 50 for GY and 50 for WAASB |========== | 52% 00:00:00 Ranks considering 55 for GY and 45 for WAASB |========== | 54% 00:00:00 Ranks considering 55 for GY and 45 for WAASB |=========== | 56% 00:00:00 Ranks considering 55 for GY and 45 for WAASB |=========== | 57% 00:00:00 Ranks considering 60 for GY and 40 for WAASB |=========== | 59% 00:00:00 Ranks considering 60 for GY and 40 for WAASB |=========== | 60% 00:00:00 Ranks considering 60 for GY and 40 for WAASB |============ | 62% 00:00:00 Ranks considering 65 for GY and 35 for WAASB |============ | 63% 00:00:00 Ranks considering 65 for GY and 35 for WAASB |============ | 65% 00:00:00 Ranks considering 65 for GY and 35 for WAASB |============= | 67% 00:00:00 Ranks considering 70 for GY and 30 for WAASB |============= | 68% 00:00:00 Ranks considering 70 for GY and 30 for WAASB |============= | 70% 00:00:00 Ranks considering 70 for GY and 30 for WAASB |============== | 71% 00:00:00 Ranks considering 75 for GY and 25 for WAASB |============== | 73% 00:00:00 Ranks considering 75 for GY and 25 for WAASB |============== | 75% 00:00:00 Ranks considering 75 for GY and 25 for WAASB |============== | 76% 00:00:00 Ranks considering 80 for GY and 20 for WAASB |=============== | 78% 00:00:00 Ranks considering 80 for GY and 20 for WAASB |=============== | 79% 00:00:00 Ranks considering 80 for GY and 20 for WAASB |=============== | 81% 00:00:00 Ranks considering 85 for GY and 15 for WAASB |================ | 83% 00:00:00 Ranks considering 85 for GY and 15 for WAASB |================ | 84% 00:00:00 Ranks considering 85 for GY and 15 for WAASB |================ | 86% 00:00:00 Ranks considering 90 for GY and 10 for WAASB |================= | 87% 00:00:00 Ranks considering 90 for GY and 10 for WAASB |================= | 89% 00:00:00 Ranks considering 90 for GY and 10 for WAASB |================= | 90% 00:00:00 Ranks considering 95 for GY and 5 for WAASB |================== | 92% 00:00:00 Ranks considering 95 for GY and 5 for WAASB |=================== | 94% 00:00:00 Ranks considering 95 for GY and 5 for WAASB |=================== | 95% 00:00:00 Ranks considering 100 for GY and 0 for WAASB |================== | 97% 00:00:00 Ranks considering 100 for GY and 0 for WAASB |===================| 98% 00:00:00 Ranks considering 100 for GY and 0 for WAASB |===================| 100% 00:00:00
# }