Print the ge_reg object in two ways. By default, the results are shown
in the R console. The results can also be exported to the directory into a
*.txt file.
Usage
# S3 method for class 'ge_reg'
print(x, export = FALSE, file.name = NULL, digits = 3, ...)Arguments
- x
An object of class
ge_reg.- export
A logical argument. If
TRUE, a *.txt file is exported to the working directory.- file.name
The name of the file if
export = TRUE- digits
The significant digits to be shown.
- ...
Options used by the tibble package to format the output. See
tibble::print()for more details.
Author
Tiago Olivoto tiagoolivoto@gmail.com
Examples
# \donttest{
library(metan)
model <- ge_reg(data_ge2, ENV, GEN, REP, PH)
#> Evaluating trait PH |============================================| 100% 00:00:00
print(model)
#> Variable PH
#> ---------------------------------------------------------------------------
#> Joint-regression Analysis of variance
#> ---------------------------------------------------------------------------
#> # A tibble: 20 × 6
#> SV Df `Sum Sq` `Mean Sq` `F value` `Pr(>F)`
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 "Total" 51 15.0 0.294 NA NA
#> 2 "GEN" 12 1.86 0.155 0.870 0.585
#> 3 "ENV + (GEN x ENV)" 39 13.1 0.336 NA NA
#> 4 "ENV (linear)" 1 7.72 7.72 NA NA
#> 5 " GEN x ENV (linear)" 12 0.755 0.0629 0.352 0.969
#> 6 "Pooled deviation" 26 4.64 0.179 NA NA
#> 7 "H1" 2 0.471 0.235 10.5 0.0000756
#> 8 "H10" 2 0.236 0.118 5.25 0.00685
#> 9 "H11" 2 0.211 0.106 4.71 0.0112
#> 10 "H12" 2 0.450 0.225 10.0 0.000110
#> 11 "H13" 2 0.410 0.205 9.15 0.000231
#> 12 "H2" 2 0.534 0.267 11.9 0.0000241
#> 13 "H3" 2 0.584 0.292 13.0 0.00000995
#> 14 "H4" 2 0.354 0.177 7.89 0.000671
#> 15 "H5" 2 0.140 0.0701 3.13 0.0484
#> 16 "H6" 2 0.334 0.167 7.44 0.000994
#> 17 "H7" 2 0.241 0.121 5.38 0.00609
#> 18 "H8" 2 0.505 0.253 11.3 0.0000403
#> 19 "H9" 2 0.172 0.0861 3.84 0.0249
#> 20 "Pooled error" 96 2.15 0.0224 NA NA
#> ---------------------------------------------------------------------------
#> Regression parameters
#> ---------------------------------------------------------------------------
#> # A tibble: 13 × 10
#> GEN b0 b1 `t(b1=1)`[,1] pval_t[,1] s2di `F(s2di=0)` pval_f RMSE
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 H1 2.62 0.806 -0.997 0.321 0.0710 10.5 7.56e-5 0.198
#> 2 H10 2.31 1.22 1.12 0.265 0.0318 5.25 6.85e-3 0.140
#> 3 H11 2.39 1.08 0.411 0.682 0.0278 4.71 1.12e-2 0.133
#> 4 H12 2.44 0.465 -2.75 0.00711 0.0676 10.0 1.10e-4 0.194
#> 5 H13 2.54 0.306 -3.57 0.000558 0.0609 9.15 2.31e-4 0.185
#> 6 H2 2.60 0.963 -0.188 0.851 0.0815 11.9 2.41e-5 0.211
#> 7 H3 2.59 1.35 1.83 0.0711 0.0898 13.0 9.95e-6 0.221
#> 8 H4 2.58 1.27 1.38 0.171 0.0515 7.89 6.71e-4 0.172
#> 9 H5 2.57 1.17 0.887 0.378 0.0159 3.13 4.84e-2 0.108
#> 10 H6 2.56 0.936 -0.330 0.742 0.0481 7.44 9.94e-4 0.167
#> 11 H7 2.40 0.992 -0.0393 0.969 0.0328 5.38 6.09e-3 0.142
#> 12 H8 2.33 1.01 0.0720 0.943 0.0767 11.3 4.03e-5 0.205
#> 13 H9 2.36 1.42 2.18 0.0317 0.0212 3.84 2.49e-2 0.120
#> # ℹ 1 more variable: R2 <dbl>
#> ---------------------------------------------------------------------------
#> Variance of b0: 0.001868774
#> Variance of b1: 0.03777002
#>
#>
#>
# }