Common functions for geese and flock. — geese-common • geese

Common functions for geese and flock.

init_model(p, verb = 80L)

nterms(p)

nnodes(p)

ntrees(p)

nleafs(p)

likelihood(p, par, as_log = FALSE, trunc_seq = TRUE, ncores = 1L)

get_probabilities(p)

get_sequence(p, reduced_sequence = TRUE)

set_seed(p, s)

sim_geese(p, par, seed = -1L)

observed_counts(p)

print_observed_counts(p)

support_size(p)

parse_polytomies(p, verbose = TRUE)

nfuns(p)

# S3 method for geese
names(p)

predict_geese(
  p,
  par,
  leave_one_out = FALSE,
  use_reduced_sequence = TRUE,
  only_annotated = FALSE
)

predict_flock(
  p,
  par,
  leave_one_out = FALSE,
  use_reduced_sequence = TRUE,
  only_annotated = FALSE
)

predict_geese_simulate(p, par, nsim, use_reduced_sequence = TRUE, seed = -1L)

# S3 method for flock
names(x)

# S3 method for geese
print(x, ...)

print_nodes(x, ...)

# S3 method for flock
print(x, ...)

Arguments

p: An object of class geese or flock.
verb: Integer scalar. When >1, it will print a progress bar during the initialization of the process of length verb.
par: Numeric vector of length nterms().
trunc_seq: When TRUE uses the truncated pruning sequence (see details).

Value

nterms returns the number of terms included in the model. This is different from the number of parameters as the later includes the number of functions in the data.

nnodes returns the number of nodes in the data, this includes internal nodes. If p is a flock, then it will return a vector of length ntrees().

ntrees returns the number of trees in the model. For a geese object this will be equal to one.

Details

init_model initializes the model. This triggers the calculation of the support using the vector of terms included. Initializing a model can only be done once.

Using the truncated pruning sequence (trunc_seq = TRUE) involves traversing the trees throught the induced subtree. This is relevant in the case that not all the leafs are annotated.