The combination of `land1` and `land2` are a key to the scores, i.e. if a bullet has six lands, each of the input vectors should have length 36.

bullet_to_land_predict(land1, land2, scores, difference, alpha = 0.05,
  addNA = FALSE)

Arguments

land1

(numeric) vector with land ids of bullet 1

land2

(numeric) vector with land ids of bullet 2

scores

numeric vector of scores to be summarized into a single number

difference

numeric value describing the minimal difference between scores from same source versus different sources.

alpha

numeric value describing the significance level for the bootstrap

addNA

how are missing values treated? addNA = TRUE leaves missing values, addNA=FALSE imputes with 0.

Value

numeric vector of binary prediction whether two lands are same-source. Vector has the same length as the input vectors.