tests/testthat/_snaps/kernels.md

In EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

lin_incr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
       [,1]
  [1,]    1
  [2,]    2
  [3,]    3
  [4,]    4
  [5,]    5

lin_incr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
       [,1]
  [1,]    1
  [2,]    2
  [3,]    3
  [4,]    4
  [5,]    5

lin_decr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
       [,1]
  [1,]   -1
  [2,]   -2
  [3,]   -3
  [4,]   -4
  [5,]   -5

lin_decr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
       [,1]
  [1,]   -1
  [2,]   -2
  [3,]   -3
  [4,]   -4
  [5,]   -5

exp_decr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
              [,1]
  [1,] 0.367879441
  [2,] 0.135335283
  [3,] 0.049787068
  [4,] 0.018315639
  [5,] 0.006737947

exp_decr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
              [,1]
  [1,] 0.367879441
  [2,] 0.135335283
  [3,] 0.049787068
  [4,] 0.018315639
  [5,] 0.006737947

exp_incr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
            [,1]
  [1,] 0.6321206
  [2,] 0.8646647
  [3,] 0.9502129
  [4,] 0.9816844
  [5,] 0.9932621

exp_incr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
            [,1]
  [1,] 0.6321206
  [2,] 0.8646647
  [3,] 0.9502129
  [4,] 0.9816844
  [5,] 0.9932621

pow_decr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
            [,1]
  [1,] 0.5000000
  [2,] 0.3333333
  [3,] 0.2500000
  [4,] 0.2000000
  [5,] 0.1666667

pow_decr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
            [,1]
  [1,] 0.5000000
  [2,] 0.3333333
  [3,] 0.2500000
  [4,] 0.2000000
  [5,] 0.1666667

pow_incr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
            [,1]
  [1,] 0.5000000
  [2,] 0.6666667
  [3,] 0.7500000
  [4,] 0.8000000
  [5,] 0.8333333

pow_incr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
            [,1]
  [1,] 0.5000000
  [2,] 0.6666667
  [3,] 0.7500000
  [4,] 0.8000000
  [5,] 0.8333333

poly2_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
       [,1]
  [1,]    2
  [2,]    6
  [3,]   12
  [4,]   20
  [5,]   30

poly2_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
       [,1]
  [1,]    2
  [2,]    6
  [3,]   12
  [4,]   20
  [5,]   30

poly3_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
       [,1]
  [1,]    3
  [2,]   14
  [3,]   39
  [4,]   84
  [5,]  155

poly3_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
       [,1]
  [1,]    3
  [2,]   14
  [3,]   39
  [4,]   84
  [5,]  155

poly4_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
        [,1]
  [1,]   3.1
  [2,]  15.6
  [3,]  47.1
  [4,] 109.6
  [5,] 217.5

poly4_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
        [,1]
  [1,]   3.1
  [2,]  15.6
  [3,]  47.1
  [4,] 109.6
  [5,] 217.5

delta_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
       [,1]
  [1,] 0.50
  [2,] 0.50
  [3,] 0.60
  [4,] 0.60
  [5,] 0.68

delta_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
       [,1]
  [1,] 0.50
  [2,] 0.50
  [3,] 0.60
  [4,] 0.60
  [5,] 0.68

delta2lr_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
         [,1]
  [1,] 0.5000
  [2,] 0.5000
  [3,] 0.7500
  [4,] 0.7500
  [5,] 0.5625

delta2lr_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
         [,1]
  [1,] 0.5000
  [2,] 0.5000
  [3,] 0.7500
  [4,] 0.7500
  [5,] 0.5625

delta2kernel_R

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "R"))
Output
            [,1]
  [1,] 0.8000000
  [2,] 0.8100000
  [3,] 0.9500000
  [4,] 0.9750000
  [5,] 0.9875000
  [6,] 0.4937500
  [7,] 0.2468750
  [8,] 0.1234375

delta2kernel_Rcpp

Code
  matrix(apply_kernel(kernel_pars, emc, mode = "Rcpp"))
Output
            [,1]
  [1,] 0.8000000
  [2,] 0.8100000
  [3,] 0.9500000
  [4,] 0.9750000
  [5,] 0.9875000
  [6,] 0.4937500
  [7,] 0.2468750
  [8,] 0.1234375

EMC2 documentation built on Jan. 12, 2026, 5:07 p.m.