Use the method M4 in Bernal Vasquez (2016). Bonferroni Holm test to judge residuals standardized by the re scaled MAD (BH MADR).
outliers_remove(data, trait, model)
| data | Experimental design data frame with the factors and traits. |
|---|---|
| trait | Name of the trait. |
| model | The fixed or random effects in the model. |
list. 1. Table with date without outliers. 2. The outliers in the dataset.
Function to remove outliers in MET experiments
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.
library(inti) library(agridat) outliers <- outliers_remove( data = john.alpha , trait ="yield" , model = "rep + (1|rep:block) + gen" ) outliers#> $data #> rep block gen yield #> 1 R1 B1 G11 4.1172 #> 2 R1 B1 G04 4.4461 #> 4 R1 B1 G22 4.5784 #> 5 R1 B2 G21 4.6540 #> 6 R1 B2 G10 4.1736 #> 7 R1 B2 G20 4.0141 #> 8 R1 B2 G02 4.3350 #> 9 R1 B3 G23 4.2323 #> 10 R1 B3 G14 4.7572 #> 11 R1 B3 G16 4.4906 #> 12 R1 B3 G18 3.9737 #> 13 R1 B4 G13 4.2530 #> 14 R1 B4 G03 3.3420 #> 15 R1 B4 G19 4.7269 #> 17 R1 B5 G17 4.7876 #> 18 R1 B5 G15 5.0902 #> 19 R1 B5 G07 4.1505 #> 20 R1 B5 G01 5.1202 #> 21 R1 B6 G06 4.7085 #> 22 R1 B6 G12 5.2560 #> 24 R1 B6 G09 3.3986 #> 25 R2 B1 G08 3.9926 #> 26 R2 B1 G20 3.6056 #> 27 R2 B1 G14 4.5294 #> 28 R2 B1 G04 4.3599 #> 29 R2 B2 G24 3.9039 #> 30 R2 B2 G15 4.9114 #> 31 R2 B2 G03 3.7999 #> 32 R2 B2 G23 4.3042 #> 33 R2 B3 G12 5.3127 #> 34 R2 B3 G11 5.1163 #> 35 R2 B3 G21 5.3802 #> 36 R2 B3 G17 5.0744 #> 37 R2 B4 G05 5.1202 #> 38 R2 B4 G09 4.2955 #> 39 R2 B4 G10 4.9057 #> 40 R2 B4 G01 5.7161 #> 41 R2 B5 G02 5.1566 #> 42 R2 B5 G18 5.0988 #> 43 R2 B5 G13 5.4840 #> 44 R2 B5 G22 5.0969 #> 45 R2 B6 G19 5.3148 #> 46 R2 B6 G07 4.6297 #> 47 R2 B6 G06 5.1751 #> 48 R2 B6 G16 5.3024 #> 49 R3 B1 G11 3.9205 #> 50 R3 B1 G01 4.6512 #> 51 R3 B1 G14 4.3887 #> 52 R3 B1 G19 4.5552 #> 53 R3 B2 G02 4.0510 #> 54 R3 B2 G15 4.6783 #> 55 R3 B2 G09 3.1407 #> 56 R3 B2 G08 3.9821 #> 57 R3 B3 G17 4.3234 #> 58 R3 B3 G18 4.2486 #> 59 R3 B3 G04 4.3960 #> 60 R3 B3 G06 4.2474 #> 61 R3 B4 G12 4.1746 #> 62 R3 B4 G13 4.7512 #> 63 R3 B4 G10 4.0875 #> 64 R3 B4 G23 3.8721 #> 65 R3 B5 G21 4.4130 #> 66 R3 B5 G22 4.2397 #> 67 R3 B5 G16 4.3852 #> 68 R3 B5 G24 3.5655 #> 69 R3 B6 G03 2.8873 #> 70 R3 B6 G05 4.1972 #> 71 R3 B6 G20 3.7349 #> 72 R3 B6 G07 3.6096 #> #> $outliers #> rep block gen yield resi res_MAD rawp.BHStud index adjp #> 3 R1 B1 G05 5.8757 0.7022176 4.929351 8.250342e-07 3 8.250342e-07 #> 16 R1 B4 G08 4.9989 0.5179535 3.635874 2.770401e-04 16 2.770401e-04 #> 23 R1 B6 G24 4.9577 0.5385472 3.780435 1.565546e-04 23 1.565546e-04 #> bholm out_flag #> 3 5.940247e-05 OUTLIER #> 16 1.939281e-02 OUTLIER #> 23 1.111538e-02 OUTLIER #>