Support-vector regression for genomic prediction

Support-vector regression for genomic prediction

Usage

morie_svm_genomic(x, y, markers, C = 1, epsilon = 0.1, gamma = "scale")

Arguments

x

Optional fixed-effect features.

y

Numeric response.

markers

(n x m) genotype matrix.

C

Cost (default 1).

epsilon

SVR tube width (default 0.1).

gamma

RBF kernel scale ("scale" = 1/(m * var(M)) or numeric).

Value

list(estimate, y_hat, alpha, support_indices, se, n, method).

References

Vapnik (1995); Montesinos Lopez Ch 7.

Examples

morie_svm_genomic(x = rnorm(50), y = rnorm(50), markers = matrix(sample(0:2, 200, TRUE), 50, 4))
#> $estimate
#> [1] -0.07929812
#> 
#> $y_hat
#>  [1] -0.273027642 -0.561089472  0.475248253  0.400414153  0.698548180
#>  [6] -0.133104503 -0.221165805  0.122331199 -0.535369445  0.094462831
#> [11] -0.772626193 -0.411409640  0.247457760  0.932182819  0.381304295
#> [16] -0.404985646  0.516494757 -0.277572833 -1.113996674  0.197624621
#> [21] -0.349392495 -0.092770296 -0.007913491 -0.495288406 -0.337243544
#> [26] -0.041319142 -0.087934233 -0.747730533  0.370020589  0.238931317
#> [31]  0.852570800 -0.398470267  0.276054252  0.361227000 -0.448432788
#> [36]  0.484348734  0.227979680  0.493013392  0.700881365 -0.544312839
#> [41] -1.182839459 -0.479484229 -1.130263081 -0.060869998 -0.506363187
#> [46] -0.051585756 -0.717326597  0.064177354 -0.560779729  0.844488622
#> 
#> $alpha
#>  [1] -0.22211809 -1.00000000  0.34298293 -1.00000000  1.00000000  0.95166987
#>  [7]  1.00000000 -0.21459923 -1.00000000  0.60366157 -1.00000000  1.00000000
#> [13] -0.69208551  1.00000000  0.59621034 -1.00000000  0.67270034 -1.00000000
#> [19] -1.00000000  0.02426795 -0.20715123  0.18269697 -0.46354572 -1.00000000
#> [25] -0.21477141  1.00000000 -1.00000000  1.00000000  0.54113242  1.00000000
#> [31]  0.02252446  0.24597169 -0.05541173 -0.80342710  1.00000000  1.00000000
#> [37]  1.00000000  1.00000000  1.00000000 -0.78611277 -0.66355882 -0.68763125
#> [43] -1.00000000 -1.00000000  0.20234378 -1.00000000  0.10110230 -0.47685174
#> [49]  1.00000000
#> 
#> $support_indices
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 24 25 26
#> [26] 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
#> 
#> $intercept
#> [1] -0.05531485
#> 
#> $se
#> [1] 0.6007547
#> 
#> $n
#> [1] 50
#> 
#> $method
#> [1] "e1071 eps-SVR (RBF)"
#>