Calcuates Genotype by Environment Interaction Means
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)
Author
Muhammad Yaseen (myaseen208@gmail.com)
Examples
data(Maiz)
ge_mean(
.data = Maiz
, .y = y
, .gen = entry
, .env = site
)
#> $ge_means
#> 1 2 3 4 5 6 7 8
#> [1,] 3621.550 3728.325 5554.025 4565.575 4379.800 6436.725 2832.400 6011.400
#> [2,] 3426.450 3918.650 4936.675 4962.575 5201.475 6036.275 2514.600 5277.700
#> [3,] 3445.850 4082.125 5117.025 5136.275 4177.925 6458.800 3529.075 4730.750
#> [4,] 3719.900 4539.175 4542.500 6029.500 5672.250 6677.800 2997.600 2516.225
#> [5,] 3164.625 4078.850 6172.525 5831.000 5413.550 6881.700 3555.600 2731.600
#> [6,] 4116.075 4877.550 5204.825 5979.900 5591.350 6915.950 3948.875 2982.575
#> [7,] 3354.025 4767.025 5389.025 4342.275 4277.175 6744.550 3536.875 4205.575
#> [8,] 4528.775 3393.250 5248.075 4441.500 4476.400 4986.250 3087.675 4483.900
#> [9,] 3135.525 4500.050 3779.600 5781.375 5407.150 5609.700 3061.375 3309.425
#> 9 10 11 12 13 14 15 16
#> [1,] 4646.700 3099.875 4432.850 6873.275 6720.550 5848.575 4600.925 5009.675
#> [2,] 4713.900 2971.750 4348.525 7570.900 5626.975 5932.475 4125.825 5196.450
#> [3,] 5447.500 2785.375 4526.200 7727.025 6293.875 5886.475 4537.400 5455.475
#> [4,] 4863.925 2843.325 7117.225 8385.050 7331.725 6439.375 6331.175 6351.100
#> [5,] 5588.350 2688.000 5995.175 8105.600 7173.575 6358.975 6327.975 6069.800
#> [6,] 5602.725 3023.500 6150.275 7636.575 7261.925 6380.225 5961.350 5730.175
#> [7,] 4318.200 2888.925 5051.575 7443.575 5543.850 5819.775 4345.925 5013.425
#> [8,] 4001.050 3353.125 3712.975 5815.825 4116.550 5522.450 4321.200 4551.000
#> [9,] 5553.450 2773.950 6429.925 8090.675 6919.875 6282.350 4889.475 5278.375
#> 17 18 19 20
#> [1,] 4414.850 3344.475 1632.000 4587.025
#> [2,] 4210.550 4415.200 2281.750 4396.475
#> [3,] 4749.175 4294.600 3059.175 5018.175
#> [4,] 5160.850 5617.700 2232.600 4987.975
#> [5,] 5454.375 4497.800 3072.525 5775.875
#> [6,] 5807.050 5333.025 3011.025 5088.475
#> [7,] 3861.575 5276.350 3210.550 4056.075
#> [8,] 5243.000 2940.375 2634.350 4806.175
#> [9,] 4988.775 5244.400 2734.950 4822.275
#>
#> $grand_mean
#> [1] 4858.138
#>