| full_indep {stagedtrees} | R Documentation | 
Full and independent staged event tree
Description
Build fitted staged event tree from data.
Usage
full(
  data,
  order = NULL,
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
## S3 method for class 'table'
full(
  data,
  order = names(dimnames(data)),
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
## S3 method for class 'data.frame'
full(
  data,
  order = colnames(data),
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
indep(
  data,
  order = NULL,
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
## S3 method for class 'table'
indep(
  data,
  order = names(dimnames(data)),
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
## S3 method for class 'data.frame'
indep(
  data,
  order = colnames(data),
  join_unobserved = TRUE,
  lambda = 0,
  name_unobserved = "UNOBSERVED"
)
Arguments
| data | data to create the model, data.frame or table. | 
| order | character vector, order of variables. | 
| join_unobserved | logical, if situations with zero observations should be joined (default TRUE). | 
| lambda | smoothing coefficient (default 0). | 
| name_unobserved | name to pass to  | 
Details
Functions to create full or independent staged tree models from
data.
The full (or saturated) staged tree is the model where every
situation is in a different stage, and thus the model has the
maximum number of parameters.
Conversely, the independent staged tree (indep) assigns
all the situations related to the same variable to the same
stage, thus it is equivalent to the independence factorization.
Examples
## full model
DD <- generate_xor_dataset(4, 100)
model_full <- full(DD, lambda = 1)
## independence model (data.frame)
DD <- generate_xor_dataset(4, 100)
model <- indep(DD, lambda = 1)
model
[Package stagedtrees version 2.3.0 Index]