GP posterior mean with Matern kernel.

GP posterior mean with Matern kernel.

Usage

morie_ghosal_gp_matern(
  x,
  y,
  nu = 1.5,
  length_scale = NULL,
  sigma_f = 1,
  noise = NULL,
  x_star = NULL
)

Arguments

x

Numeric vector or matrix of input points.

y

Numeric response vector.

nu

Matern smoothness parameter (default 1.5).

length_scale

Optional kernel length-scale.

sigma_f

Numeric signal sd (default 1).

noise

Optional observation noise sd.

x_star

Optional matrix of prediction points (defaults to x).

Value

Named list with estimate, se, mu, sd, length_scale, nu, noise, n, method.

Examples

morie_ghosal_gp_matern(x = rnorm(50), y = rnorm(50))
#> $estimate
#> [1] 0.1173324
#> 
#> $se
#> [1] 0.06050369
#> 
#> $mu
#>  [1]  0.033591020  0.332157047  0.561662053  0.815655945  0.119265152
#>  [6] -0.078342184 -1.835024143  0.801023936 -0.249679978  0.365929034
#> [11] -0.206250186  0.717186184  0.794665891  0.118162328  0.226691531
#> [16]  0.238221716 -0.308300917 -0.135665484 -0.053154530 -0.341867753
#> [21]  1.149071363  0.808331285  2.057826078  0.397014432  0.641625846
#> [26]  0.193333792  0.009182752 -0.473232837 -0.372334794  0.032989058
#> [31]  0.035324236 -0.259025051 -0.514237368  0.425173891  0.032855911
#> [36]  0.273279278  0.449225956 -0.636472190 -0.268476490 -0.111727436
#> [41] -0.425937845 -0.475829071 -0.109512631 -0.104885541 -0.129236307
#> [46] -0.407442183  0.443705374  0.579965243  0.762408750 -0.052271363
#> 
#> $sd
#>  [1] 0.04204272 0.05492810 0.07777175 0.05735425 0.06355397 0.05668159
#>  [7] 0.10181785 0.04835667 0.09118174 0.05626054 0.07487770 0.06735609
#> [13] 0.04930579 0.06504100 0.07463431 0.05735711 0.09502229 0.05255291
#> [19] 0.10083911 0.05687034 0.09877748 0.05555015 0.09878656 0.06241486
#> [25] 0.05166670 0.05035201 0.05815755 0.05987382 0.05992783 0.04382951
#> [31] 0.04427414 0.05629413 0.05063540 0.05458406 0.04219593 0.05264688
#> [37] 0.06293756 0.05237696 0.05326860 0.04946629 0.05316228 0.06719490
#> [43] 0.05297204 0.04382021 0.04432129 0.05291831 0.06469482 0.05334884
#> [49] 0.04789580 0.04303369
#> 
#> $length_scale
#> [1] 0.8995316
#> 
#> $nu
#> [1] 1.5
#> 
#> $noise
#> [1] 0.102834
#> 
#> $n
#> [1] 50
#> 
#> $method
#> [1] "GP regression (Matern kernel)"
#>