Use the method M4 in Bernal Vasquez (2016). Bonferroni Holm test to judge
residuals standardized by the re scaled MAD (BH MADR).
Usage
outliers_remove(data, trait, model)
Arguments
- data
Experimental design data frame with the factors and traits.
- trait
Name of the trait.
- model
The fixed or random effects in the model.
Value
list. 1. Table with date without outliers. 2. The outliers in the
dataset.
Details
Function to remove outliers in MET experiments
References
Bernal Vasquez, Angela Maria, et al. “Outlier Detection Methods for
Generalized Lattices: A Case Study on the Transition from ANOVA to REML.”
Theoretical and Applied Genetics, vol. 129, no. 4, Apr. 2016.
Examples
library(inti)
rmout <- outliers_remove(
data = potato
, trait ="stemdw"
, model = "0 + (1|bloque) + geno"
)
rmout$outliers
#> bloque geno stemdw resi res_MAD rawp.BHStud index adjp bholm out_flag
#> 68 IV G05 80.65 60.36709 18.84505 0 68 0 0 OUTLIER