selection

this is the sdm3

dm_national_choice(
  recip_matrix = NULL,
  donor_matrix = NULL,
  allocation_score = NULL,
  HLA = NULL,
  graft_number = 1,
  parameter_a = 1,
  parameter_b = 1,
  parameter_c = 1,
  quality = TRUE,
  age = TRUE,
  state = TRUE,
  bloodgroup = TRUE,
  accept_prob = NULL,
  yearly_scale = rep(1, 100)
)

Arguments

recip_matrix	a data.frame with recipient features, this is the input recipient matrix
donor_matrix	a data.frame with donor features, this is the input donor matrix
allocation_score	a vector, this is the score for each pair
HLA	a matrix, this is the calculated HLA mismatching counts matrix
graft_number	a numerical value, this is the graft number
parameter_a	an interger hyperparameter to tune
parameter_b	an interger hyperparameter to tune
parameter_c	an interger hyperparameter to tune
quality	a boolean value, TRUE/FALSE, quality measure indicator
age	a boolean value, TRUE/FALSE, age indicator
state	a boolean value, TRUE/FALSE, state indicator
bloodgroup	a boolean value, TRUE/FALSE, blood group indicator
accept_prob	a numerical value between 0 and 1, which is a user defined minimum acceptence probability, then for different recipient, we randomly sample from this value to 1, the default value is NULL, which means we give an accept rate based on HLA matchability
yearly_scale	a vector representing yearly scale, this allows the user to define different accpetence rate for different years

Value

a data.frame with matched recipient

Examples

data("rawdata", package = "simKAP")
data("newdata", package = "simKAP")
HLA_matrix <- hla_match(raw_recip_matrix_subset, raw_donor_matrix[1,])

selected <- dm_national_choice(raw_recip_matrix_subset,raw_donor_matrix[1,],
allocation_score=allocation_national(raw_recip_matrix_subset,raw_donor_matrix[1,],HLA_matrix),
HLA_matrix,1,1,1,1,TRUE,TRUE,TRUE,TRUE,accept_prob = NULL, yearly_scale=rep(1, 100));
#> Warning: no non-missing arguments to min; returning Inf