Boostrap for Model Predictions

Bootstrap function which compute proportion by species fishing mode and ocean for confindence interval

tunaboot(
  sample_data,
  allset_data,
  Ntree = 1000,
  Nmtry = 2,
  Nseed = 7,
  min_node = 5,
  Nboot = 10,
  Nseed_boot,
  target_period
)

Arguments

sample_data: (data frame) Data used for the modelling. Output table from process 3.1.
allset_data: (data frame) Data used for prediction.Output table from process 3.4.
Ntree: (integer) Number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times. The default value is 1000.
Nmtry: Number of variables randomly sampled as candidates at each split. The default value is 2.
Nseed: Set the initial seed for the modelling. The default value is 7.
min_node: Minimum size of terminal nodes. Setting this number larger causes smaller trees to be grown (and thus take less time).The default value is 5.
Nboot: The number of bootstrap samples desired. The fefault value is 10
Nseed_boot: Set the initial seed for the modelling. The default value is equal to Nseed parameter
target_period: Time period for the predictions in year. Default is the year of the data to predict

TODO