Calcuates Genotype by Environment Interaction Means

# S3 method for default
ge_mean(.data, .y, .gen, .env)

Arguments

.data

data.frame

.y

Response Variable

.gen

Genotypes Factor

.env

Environment Factor

Value

Genotype by Environment Interaction Means

References

Perez-Elizalde, S., Jarquin, D., and Crossa, J. (2011) A General Bayesian Estimation Method of Linear–Bilinear Models Applied to Plant Breeding Trials With Genotype × Environment Interaction. Journal of Agricultural, Biological, and Environmental Statistics, 17, 15–37. (doi:10.1007/s13253-011-0063-9)

Examples

data(cultivo2008) ge_mean( .data = cultivo2008 , .y = y , .gen = entry , .env = site )
#> $ge_means #> 1 2 3 4 5 6 7 8 #> [1,] 3652.937 2652.312 4215.066 5030.928 3717.742 4265.214 1144.147 4581.738 #> [2,] 3584.441 3337.220 4201.519 4759.513 4735.639 5911.388 3172.906 4576.509 #> [3,] 2957.619 2603.306 4457.343 4016.567 2842.543 5222.392 3352.109 4422.882 #> [4,] 3343.400 3417.552 4433.719 3574.744 4452.240 5827.206 1411.765 5065.913 #> [5,] 3741.396 2941.125 4449.263 3969.509 5623.957 6709.235 2971.836 5655.611 #> [6,] 4112.109 3291.208 4716.543 3821.442 5535.734 5530.171 2405.704 5641.541 #> [7,] 4199.713 3117.474 5258.042 3860.895 6143.316 6204.383 3797.504 5236.129 #> [8,] 3373.346 3469.458 4663.020 3604.215 5734.046 6593.729 1114.201 5772.876 #> [9,] 3263.258 3385.419 4128.983 3513.664 5305.573 5934.727 1590.493 4848.923 #> [10,] 2979.057 3223.045 3860.467 3089.667 4785.264 5458.110 1338.562 6119.727 #> [11,] 3172.660 2677.885 4184.835 2821.341 5272.870 4738.788 2734.165 4035.437 #> [12,] 3213.586 2059.809 4241.399 3223.711 5314.415 5235.559 1741.176 5613.497 #> 9 10 11 12 13 14 15 16 #> [1,] 3721.497 3810.652 2747.475 2214.150 2286.393 2527.908 1188.3366 3540.853 #> [2,] 2033.892 4307.328 3353.535 2475.869 1710.517 4287.120 1529.2077 5488.614 #> [3,] 3487.962 5065.485 2343.434 3023.833 1911.824 2885.145 1540.9266 3321.371 #> [4,] 3112.014 4035.960 3757.576 1921.820 2304.456 2739.929 1301.2224 2729.298 #> [5,] 3350.826 4592.861 2222.222 2551.447 2109.804 3154.188 1520.2904 4131.266 #> [6,] 2702.507 3535.434 3151.515 2474.918 1923.708 3657.687 1695.9273 4076.597 #> [7,] 3650.529 5926.979 3151.515 3277.233 1907.308 3891.296 1627.8341 5308.290 #> [8,] 2705.502 2588.665 3272.727 2721.283 2305.407 2810.649 1128.2604 2425.687 #> [9,] 2556.673 4853.058 4323.232 1854.418 2332.026 3086.612 1420.2886 2719.012 #> [10,] 1490.244 4081.212 2101.010 1754.123 2305.407 2351.009 1530.4316 3312.487 #> [11,] 1334.379 4114.200 1858.586 2053.107 2312.062 2538.056 963.8316 3231.943 #> [12,] 2552.062 4413.042 1131.313 1548.351 1951.990 2368.558 1104.1204 2789.733 #> 17 18 19 20 21 22 23 #> [1,] 2949.495 5717.404 2021.878 2868.687 1535.3535 9902.857 6356.965 #> [2,] 4363.636 6982.647 2850.859 3838.384 1696.9697 11550.695 10567.563 #> [3,] 4565.657 6232.713 2788.876 3393.939 1171.7172 9125.307 6510.973 #> [4,] 4646.465 5982.783 2482.238 3797.980 1171.7172 9459.704 7498.478 #> [5,] 4363.636 5181.751 2497.069 3838.384 969.6970 10705.885 6771.028 #> [6,] 3797.980 5227.431 2971.594 3515.152 767.6768 10773.192 6758.289 #> [7,] 4404.040 6710.756 3437.801 3313.131 2343.4343 11131.166 7577.003 #> [8,] 4202.020 6557.223 2881.708 2383.838 2060.6061 10267.105 8224.407 #> [9,] 4242.424 5293.787 2417.450 3717.172 1898.9899 9827.041 8492.163 #> [10,] 3636.364 5355.913 2014.510 3595.960 646.4646 8763.958 8175.163 #> [11,] 3434.343 6043.103 1779.173 2949.495 1050.5051 10221.425 7444.861 #> [12,] 2545.455 4927.495 2078.775 2545.455 686.8687 8204.396 6501.419 #> 24 25 #> [1,] 3797.913 6520.266 #> [2,] 3353.477 9744.666 #> [3,] 3757.510 7753.590 #> [4,] 3191.863 7321.464 #> [5,] 2989.847 8007.964 #> [6,] 3151.460 8538.318 #> [7,] 5050.417 8816.031 #> [8,] 4403.963 9397.720 #> [9,] 3272.670 8879.037 #> [10,] 3131.258 8930.087 #> [11,] 5333.240 8871.431 #> [12,] 3919.123 10588.715 #> #> $grand_mean #> [1] 4069.25 #>