ANOVA of Eberhart & Russel’s Model
er_anova(.data, .y, .rep, .gen, .env) # S3 method for default er_anova(.data, .y, .rep, .gen, .env)
| .data | data.frame |
|---|---|
| .y | Response Variable |
| .rep | Replication Factor |
| .gen | Genotypes Factor |
| .env | Environment Factor |
Additive ANOVA
Singh, R. K. and Chaudhary, B. D. (2004) Biometrical Methods in Quantitative Genetic Analysis. New Delhi: Kalyani.
data(ge_data) Yield.er_anova <- er_anova( .data = ge_data , .y = Yield , .rep = Rep , .gen = Gen , .env = Env )#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.#> Warning: Unknown or uninitialised column: '(weights)'.#> Warning: Unknown or uninitialised column: '(offset)'.Yield.er_anova#> [[1]] #> Analysis of Variance Table #> #> Response: .data[[Y]] #> Df Sum Sq Mean Sq F value Pr(>F) #> Env 10 263940496 26394050 68.0551 1.995e-08 *** #> Rep(Env) 11 4266167 387833 3.9109 1.658e-05 *** #> Gen 59 71662431 1214617 12.2482 < 2.2e-16 *** #> Gen:Env 590 201336476 341248 3.4411 < 2.2e-16 *** #> Residuals 649 64359568 99167 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #> #> $er_anova #> Df Sum Sq Mean Sq F value Pr(>F) #> Total 659 234771569 356254 #> Gen 59 2133083 36154 0.4497 0.999871 #> Env + (Gen x Env) 600 232638486 387731 #> Env (linear) 1 131970248 131970248 #> Gen x Env(linear) 59 57257951 970474 12.0722 < 2.2e-16 *** #> Pooled deviation 540 43410287 80389 #> 013BT034 9 471024 52336 1.0734 0.380296 #> 122557 9 287034 31893 0.6541 0.750685 #> 122559 9 899838 99982 2.0506 0.031866 * #> 12B.2511 9 800492 88944 1.8242 0.060823 . #> 12FJ26 9 686360 76262 1.5641 0.122229 #> 14B.1030 9 668473 74275 1.5234 0.135661 #> 14C036 9 1110265 123363 2.5301 0.007408 ** #> 14C040 9 722512 80279 1.6465 0.098562 . #> 9496 9 495207 55023 1.1285 0.339863 #> AUR0809 9 541979 60220 1.2351 0.270158 #> AUR0810 9 979857 108873 2.2330 0.018531 * #> AZRC11 9 771590 85732 1.7583 0.072941 . #> AZRC18 9 589136 65460 1.3426 0.211227 #> AZRC20 9 1050318 116702 2.3935 0.011344 * #> BARDC1016 9 578318 64258 1.3179 0.223765 #> CT12176 9 1320714 146746 3.0097 0.001576 ** #> DANI16 9 588746 65416 1.3417 0.211669 #> DN111 9 864812 96090 1.9708 0.040168 * #> DN117 9 557660 61962 1.2708 0.249318 #> DN126 9 575662 63962 1.3119 0.226930 #> FAISALABAD08 9 896257 99584 2.0424 0.032635 * #> IVI 9 1077549 119728 2.4556 0.009356 ** #> IVII 9 1928363 214263 4.3945 1.353e-05 *** #> KT325 9 923816 102646 2.1052 0.027138 * #> KT335 9 959688 106632 2.1870 0.021279 * #> LOCAL CHECK 9 648921 72102 1.4788 0.151768 #> MSH3 9 541577 60175 1.2342 0.270708 #> NIBGE GANDUM3 9 763272 84808 1.7394 0.076811 . #> NIBGE GANDUM4 9 183983 20443 0.4193 0.925128 #> NR443 9 556283 61809 1.2677 0.251098 #> NR448 9 602418 66935 1.3728 0.196605 #> NR487 9 529356 58817 1.2063 0.287854 #> NR488 9 439359 48818 1.0012 0.437501 #> NR491 9 690621 76736 1.5738 0.119205 #> NRL1123 9 774862 86096 1.7658 0.071467 . #> NRL1206 9 715799 79533 1.6312 0.102626 #> NW181838 9 611492 67944 1.3935 0.187095 #> NW5201 9 890418 98935 2.0291 0.033926 * #> PAKISTAN13 9 991699 110189 2.2599 0.017078 * #> PR115 9 570781 63420 1.3007 0.232841 #> PR118 9 553769 61530 1.2620 0.254371 #> PR119 9 329640 36627 0.7512 0.661879 #> PR120 9 505853 56206 1.1528 0.323002 #> PR121 9 967924 107547 2.2058 0.020113 * #> QS3 9 1144963 127218 2.6092 0.005769 ** #> SD1013 9 930660 103407 2.1208 0.025915 * #> SRN13121 9 1231054 136784 2.8054 0.003074 ** #> TWS12155 9 326136 36237 0.7432 0.669305 #> TWS12245 9 474036 52671 1.0803 0.375101 #> TWS12464 9 432572 48064 0.9858 0.450346 #> UOS1 9 571017 63446 1.3013 0.232552 #> V12066 9 529175 58797 1.2059 0.288114 #> V13348 9 1202805 133645 2.7410 0.003785 ** #> V14154 9 189614 21068 0.4321 0.917993 #> V14168 9 751301 83478 1.7121 0.082705 . #> V14170 9 892534 99170 2.0340 0.033453 * #> V14225 9 463652 51517 1.0566 0.393196 #> V14227 9 700835 77871 1.5971 0.112217 #> WBG14 9 467120 51902 1.0645 0.387096 #> WV1038 9 889119 98791 2.0262 0.034219 * #> Pooled error 660 32179784 48757 #> --- #> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 #>