Print a sh object in two ways. By default, the results are shown in
the R console. The results can also be exported to the directory.
Usage
# S3 method for class 'sh'
print(x, export = FALSE, file.name = NULL, digits = 4, ...)Arguments
- x
An object of class
sh.- 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{
vcov <- covcor_design(data_g, GEN, REP, everything())
means <- as.matrix(vcov$means)
pcov <- vcov$phen_cov
gcov <- vcov$geno_cov
index <- Smith_Hazel(means, pcov = pcov, gcov = gcov, weights = rep(1, 15))
print(index)
#>
#> -----------------------------------------------------------------------------------
#> Index coefficients
#> -----------------------------------------------------------------------------------
#> # A tibble: 15 × 3
#> VAR b gen_weights
#> <chr> <dbl> <dbl>
#> 1 PH -1953. 1
#> 2 EH -465.3 1
#> 3 EP 345.2 1
#> 4 EL 251.0 1
#> 5 ED 133.3 1
#> 6 CL -229.5 1
#> 7 CD -233.7 1
#> 8 CW -176.0 1
#> 9 KW -94.02 1
#> 10 NR -82.86 1
#> 11 NKR -181.0 1
#> 12 CDED -34.27 1
#> 13 PERK -415.9 1
#> 14 TKW 53.78 1
#> 15 NKE 43.13 1
#>
#> -----------------------------------------------------------------------------------
#> Genetic worth
#> -----------------------------------------------------------------------------------
#> GEN V1
#> 1 H7 -28058.73
#> 2 H12 -28060.55
#> 3 H2 -28069.01
#> 4 H5 -28085.19
#> 5 H3 -28115.99
#> 6 H13 -28132.23
#> 7 H9 -28204.45
#> 8 H6 -28242.55
#> 9 H1 -28243.94
#> 10 H10 -28247.07
#> 11 H11 -28266.74
#> 12 H8 -28296.72
#> 13 H4 -28339.60
#>
#> -----------------------------------------------------------------------------------
#> Selection gain
#> -----------------------------------------------------------------------------------
#> # A tibble: 15 × 7
#> VAR Xo Xs SD SDperc sense goal
#> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
#> 1 PH 2.167 2.304 0.1371 6.328 increase 100
#> 2 EH 1.078 1.22 0.1420 13.18 increase 100
#> 3 EP 0.4958 0.5227 0.02689 5.423 increase 100
#> 4 EL 14.67 14.25 -0.4193 -2.859 increase 0
#> 5 ED 47.87 48.27 0.3990 0.8335 increase 100
#> 6 CL 28.45 28.02 -0.4240 -1.490 increase 0
#> 7 CD 15.77 14.99 -0.7769 -4.927 increase 0
#> 8 CW 20.78 22.55 1.765 8.494 increase 100
#> 9 KW 146.8 152.0 5.198 3.540 increase 100
#> 10 NR 15.78 15.93 0.1487 0.9422 increase 100
#> 11 NKR 30.4 29.6 -0.8000 -2.632 increase 0
#> 12 CDED 0.5946 0.5800 -0.01454 -2.445 increase 0
#> 13 PERK 87.65 87.05 -0.5997 -0.6842 increase 0
#> 14 TKW 317.7 320.8 3.122 0.9825 increase 100
#> 15 NKE 467.9 478.8 10.87 2.323 increase 100
#>
#> -----------------------------------------------------------------------------------
#> Phenotypic variance-covariance matrix
#> -----------------------------------------------------------------------------------
#> PH EH EP EL ED CL CD CW KW
#> PH 0.0280 0.0190 0.00190 0.00580 0.2189 -0.0362 -0.0287 0.139 1.970
#> EH 0.0190 0.0163 0.00285 -0.02238 0.1524 -0.0109 -0.0486 0.096 1.130
#> EP 0.0019 0.0028 0.00088 -0.01172 0.0193 0.0056 -0.0149 0.014 0.056
#> EL 0.0058 -0.0224 -0.01172 0.37517 0.1178 0.0488 0.3479 0.499 4.269
#> ED 0.2189 0.1524 0.01931 0.11785 6.1789 3.7315 0.2053 8.643 34.340
#> CL -0.0362 -0.0109 0.00562 0.04882 3.7315 4.7407 0.3090 8.619 13.099
#> CD -0.0287 -0.0486 -0.01492 0.34792 0.2053 0.3090 0.4508 0.673 3.513
#> CW 0.1388 0.0962 0.01410 0.49897 8.6429 8.6186 0.6726 20.972 49.106
#> KW 1.9698 1.1300 0.05606 4.26873 34.3402 13.0992 3.5130 49.106 274.442
#> NR 0.1514 0.1005 0.01161 -0.10612 2.1678 0.3145 -0.1293 1.771 14.432
#> NKR -0.0262 -0.0732 -0.02513 0.38921 -2.1832 -3.1529 0.4191 -4.440 -0.989
#> CDED -0.0034 -0.0021 -0.00014 0.00024 0.0013 0.0526 0.0044 0.074 -0.144
#> PERK 0.0556 0.0242 -0.00297 0.01109 -2.1099 -3.5815 -0.1025 -7.471 -6.722
#> TKW 0.4550 0.4704 0.11429 6.64529 51.1086 60.8129 7.0140 125.436 276.147
#> NKE 5.5613 2.8220 -0.00892 4.32251 36.2582 -45.2534 1.9641 -20.768 489.456
#> NR NKR CDED PERK TKW NKE
#> PH 0.151 -0.026 -0.00341 0.056 0.45 5.6e+00
#> EH 0.101 -0.073 -0.00213 0.024 0.47 2.8e+00
#> EP 0.012 -0.025 -0.00014 -0.003 0.11 -8.9e-03
#> EL -0.106 0.389 0.00024 0.011 6.65 4.3e+00
#> ED 2.168 -2.183 0.00133 -2.110 51.11 3.6e+01
#> CL 0.315 -3.153 0.05261 -3.582 60.81 -4.5e+01
#> CD -0.129 0.419 0.00444 -0.102 7.01 2.0e+00
#> CW 1.771 -4.440 0.07352 -7.471 125.44 -2.1e+01
#> KW 14.432 -0.989 -0.14378 -6.722 276.15 4.9e+02
#> NR 1.605 0.130 -0.02024 0.068 -1.47 4.9e+01
#> NKR 0.130 4.746 -0.03809 2.322 -48.48 7.0e+01
#> CDED -0.020 -0.038 0.00108 -0.049 0.65 -1.4e+00
#> PERK 0.068 2.322 -0.04859 3.426 -47.06 4.6e+01
#> TKW -1.472 -48.480 0.64659 -47.057 1180.42 -8.2e+02
#> NKE 48.839 70.119 -1.38172 45.583 -816.10 2.8e+03
#>
#> -----------------------------------------------------------------------------------
#> Genotypic variance-covariance matrix
#> -----------------------------------------------------------------------------------
#> PH EH EP EL ED CL CD CW
#> PH 0.01708 0.00888 -0.00012 3.0e-03 0.18583 -0.0556 -0.0287 0.106
#> EH 0.00888 0.00501 0.00017 -2.5e-02 0.12777 -0.0298 -0.0463 0.082
#> EP -0.00012 0.00017 0.00015 -1.2e-02 0.01583 0.0019 -0.0143 0.015
#> EL 0.00303 -0.02515 -0.01226 4.7e-02 0.00053 -0.0337 0.1487 0.090
#> ED 0.18583 0.12777 0.01583 5.3e-04 5.36879 3.3347 0.1667 7.676
#> CL -0.05561 -0.02982 0.00185 -3.4e-02 3.33474 4.2690 0.3234 8.248
#> CD -0.02873 -0.04627 -0.01425 1.5e-01 0.16666 0.3234 0.2396 0.378
#> CW 0.10646 0.08249 0.01542 9.0e-02 7.67557 8.2480 0.3784 18.458
#> KW 1.53382 0.82217 0.01174 6.2e-01 28.50002 10.8906 0.8898 37.657
#> NR 0.13286 0.08405 0.00867 -1.2e-01 1.86537 0.1827 -0.1515 1.632
#> NKR -0.08098 -0.13532 -0.04097 -2.6e-01 -2.59771 -3.2041 -0.1574 -5.468
#> CDED -0.00342 -0.00223 -0.00018 4.3e-05 0.00318 0.0477 0.0052 0.078
#> PERK 0.04600 0.01193 -0.00674 -4.3e-02 -2.05591 -3.5398 -0.1430 -7.102
#> TKW -0.21096 0.01407 0.04693 3.9e+00 44.49990 57.0469 5.8305 110.666
#> NKE 5.10010 2.44637 -0.06371 -3.5e+00 26.63104 -47.0664 -4.8728 -35.643
#> KW NR NKR CDED PERK TKW NKE
#> PH 1.534 0.1329 -0.081 -3.4e-03 0.0460 -0.211 5.100
#> EH 0.822 0.0841 -0.135 -2.2e-03 0.0119 0.014 2.446
#> EP 0.012 0.0087 -0.041 -1.8e-04 -0.0067 0.047 -0.064
#> EL 0.620 -0.1159 -0.261 4.3e-05 -0.0430 3.905 -3.468
#> ED 28.500 1.8654 -2.598 3.2e-03 -2.0559 44.500 26.631
#> CL 10.891 0.1827 -3.204 4.8e-02 -3.5398 57.047 -47.066
#> CD 0.890 -0.1515 -0.157 5.2e-03 -0.1430 5.831 -4.873
#> CW 37.657 1.6321 -5.468 7.8e-02 -7.1018 110.666 -35.643
#> KW 180.972 13.0598 -12.058 -1.2e-01 -7.9108 175.110 344.314
#> NR 13.060 1.1809 -0.184 -1.9e-02 0.0477 2.739 36.598
#> NKR -12.058 -0.1839 2.147 -3.4e-02 2.0327 -48.942 34.725
#> CDED -0.117 -0.0191 -0.034 9.6e-04 -0.0483 0.646 -1.294
#> PERK -7.911 0.0477 2.033 -4.8e-02 3.1367 -46.969 42.024
#> TKW 175.110 2.7390 -48.942 6.5e-01 -46.9689 840.939 -627.503
#> NKE 344.314 36.5977 34.725 -1.3e+00 42.0240 -627.503 1982.321
# }