mgidi
object in two ways. By default, the results are shown in
the R console. The results can also be exported to the directory.R/mgidi.R
print.mgidi.Rd
Print an object of class mgidi
Print a mgidi
object in two ways. By default, the results are shown in
the R console. The results can also be exported to the directory.
# S3 method for mgidi print(x, export = FALSE, file.name = NULL, digits = 4, ...)
x | An object of class |
---|---|
export | A logical argument. If |
file.name | The name of the file if |
digits | The significant digits to be shown. |
... | Options used by the tibble package to format the output. See
|
Tiago Olivoto tiagoolivoto@gmail.com
# \donttest{ library(metan) model <- gamem(data_g, gen = GEN, rep = REP, resp = c(KW, NR, NKE, NKR))#>#>#>#>#> --------------------------------------------------------------------------- #> P-values for Likelihood Ratio Test of the analyzed traits #> --------------------------------------------------------------------------- #> model KW NR NKE NKR #> Complete NA NA NA NA #> Genotype 0.0253 0.0056 0.00952 0.216 #> --------------------------------------------------------------------------- #> Variables with nonsignificant Genotype effect #> NKR #> ---------------------------------------------------------------------------#> #> ------------------------------------------------------------------------------- #> Principal Component Analysis #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 4 #> PC Eigenvalues `Variance (%)` `Cum. variance (%)` #> <chr> <dbl> <dbl> <dbl> #> 1 PC1 2.42 60.6 60.6 #> 2 PC2 1.19 29.8 90.3 #> 3 PC3 0.32 8 98.3 #> 4 PC4 0.07 1.66 100 #> ------------------------------------------------------------------------------- #> Factor Analysis - factorial loadings after rotation- #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 5 #> VAR FA1 FA2 Communality Uniquenesses #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 KW -0.9 0.04 0.82 0.18 #> 2 NR -0.92 -0.12 0.87 0.13 #> 3 NKE -0.7 -0.69 0.96 0.04 #> 4 NKR 0.05 -0.98 0.97 0.03 #> ------------------------------------------------------------------------------- #> Comunalit Mean: 0.9033994 #> ------------------------------------------------------------------------------- #> Selection differential #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 11 #> VAR Factor Xo Xs SD SDperc h2 SG SGperc sense goal #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> #> 1 KW FA 1 147. 163. 16.2 11.0 0.659 10.7 7.27 increase 100 #> 2 NR FA 1 15.8 17.4 1.63 10.3 0.736 1.20 7.60 increase 100 #> 3 NKE FA 1 468. 532. 64.0 13.7 0.713 45.6 9.74 increase 100 #> 4 NKR FA 2 30.4 31.2 0.814 2.68 0.452 0.368 1.21 increase 100 #> ------------------------------------------------------------------------------ #> Selected genotypes #> ------------------------------------------------------------------------------- #> H13 H5 #> -------------------------------------------------------------------------------print(mgidi_index)#> ------------------------------------------------------------------------------- #> Correlation matrix used used in factor analysis #> ------------------------------------------------------------------------------- #> KW NR NKE NKR #> KW 1.000 0.688 0.56 -0.027 #> NR 0.688 1.000 0.73 0.047 #> NKE 0.560 0.731 1.00 0.610 #> NKR -0.027 0.047 0.61 1.000 #> ------------------------------------------------------------------------------- #> Principal component analysis #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 4 #> PC Eigenvalues `Variance (%)` `Cum. variance (%)` #> <chr> <dbl> <dbl> <dbl> #> 1 PC1 2.422 60.55 60.55 #> 2 PC2 1.192 29.79 90.34 #> 3 PC3 0.3201 8.002 98.34 #> 4 PC4 0.06631 1.658 100 #> ------------------------------------------------------------------------------- #> Initial loadings #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 3 #> VAR PC1 PC2 #> <chr> <dbl> <dbl> #> 1 KW -0.7827 0.4545 #> 2 NR -0.8731 0.3232 #> 3 NKE -0.9353 -0.2852 #> 4 NKR -0.4153 -0.8939 #> ------------------------------------------------------------------------------- #> Loadings after varimax rotation #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 3 #> VAR FA1 FA2 #> <chr> <dbl> <dbl> #> 1 KW -0.9042 0.04004 #> 2 NR -0.9235 -0.1182 #> 3 NKE -0.6966 -0.6862 #> 4 NKR 0.04631 -0.9846 #> ------------------------------------------------------------------------------- #> Scores for genotypes-ideotype #> ------------------------------------------------------------------------------- #> # A tibble: 14 x 3 #> GEN FA1 FA2 #> <chr> <dbl> <dbl> #> 1 H1 -1.615 -0.2874 #> 2 H10 -0.2495 -2.888 #> 3 H11 -1.220 -2.278 #> 4 H12 -1.813 -1.450 #> 5 H13 -3.589 -2.244 #> 6 H2 -1.816 -0.6748 #> 7 H3 -0.5856 -1.045 #> 8 H4 -0.2922 -2.673 #> 9 H5 -2.432 -2.315 #> 10 H6 -1.405 0.2438 #> 11 H7 -1.449 -0.8412 #> 12 H8 -0.6321 -0.4303 #> 13 H9 0.01742 -1.398 #> 14 ID1 -3.458 -2.745 #> ------------------------------------------------------------------------------- #> Multi-trait genotype-ideotype distance index #> ------------------------------------------------------------------------------- #> # A tibble: 13 x 2 #> Genotype MGIDI #> <chr> <dbl> #> 1 H13 0.5181 #> 2 H5 1.112 #> 3 H12 2.093 #> 4 H11 2.286 #> 5 H2 2.642 #> 6 H7 2.767 #> 7 H1 3.072 #> 8 H4 3.166 #> 9 H10 3.211 #> 10 H3 3.337 #> 11 H6 3.626 #> 12 H8 3.653 #> 13 H9 3.727 #> ------------------------------------------------------------------------------- #> Selection differential #> ------------------------------------------------------------------------------- #> # A tibble: 4 x 11 #> VAR Factor Xo Xs SD SDperc h2 SG SGperc sense goal #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> #> 1 KW FA 1 146.8 163.0 16.19 11.03 0.6594 10.67 7.271 increase 100 #> 2 NR FA 1 15.78 17.42 1.630 10.33 0.7359 1.200 7.601 increase 100 #> 3 NKE FA 1 467.9 531.9 63.97 13.67 0.7126 45.58 9.742 increase 100 #> 4 NKR FA 2 30.40 31.21 0.8142 2.678 0.4523 0.3683 1.211 increase 100 #> ------------------------------------------------------------------------------- #> Selected genotypes #> ------------------------------------------------------------------------------- #> H13 H5# }