Prepare priors
Arguments
- max_antigens
integer: how many antigen-isotypes will be modeled
Value
a list with elements: "n_params": how many parameters??
"mu.hyp": ??
"prec.hyp": ??
"omega" : ??
"wishdf": Wishart distribution degrees of freedom
"prec.logy.hyp": array of hyper-parameters for the precision (inverse variance) of the biomarkers, on log-scale
Examples
prep_priors(max_antigens = 2)
#> $n_params
#> [1] 5
#>
#> $mu.hyp
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1 7 1 -4 -1
#> [2,] 1 7 1 -4 -1
#>
#> $prec.hyp
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1 0 0 0 0
#> [2,] 1 0 0 0 0
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 1e-05 0 0 0
#> [2,] 0 1e-05 0 0 0
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 1 0 0
#> [2,] 0 0 1 0 0
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 0 0.001 0
#> [2,] 0 0 0 0.001 0
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 0 0 1
#> [2,] 0 0 0 0 1
#>
#>
#> $omega
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1 0 0 0 0
#> [2,] 1 0 0 0 0
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 50 0 0 0
#> [2,] 0 50 0 0 0
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 1 0 0
#> [2,] 0 0 1 0 0
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 0 10 0
#> [2,] 0 0 0 10 0
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0 0 0 0 1
#> [2,] 0 0 0 0 1
#>
#>
#> $wishdf
#> [1] 20 20
#>
#> $prec.logy.hyp
#> [,1] [,2]
#> [1,] 4 1
#> [2,] 4 1
#>
#> attr(,"class")
#> [1] "curve_params_priors" "list"