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Shared scaffolding for the collections explored by [get_model()]/ [normal_block()]: a sweep over sparsity penalties ([`NormalBlockVarCollectionSparsity`]), over the number of clusters ([`NormalBlockVarCollectionClusters`]), or over both ([`NormalBlockVarCollectionClustersSparsity`]). Concrete subclasses set `private$progress_field`/`private$progress_label` in their `initialize()` and provide their own `get_best_model()`, delegating the (row of `self$criteria` minimizing a criterion) lookup to `private$best_id()`.

Public fields

models

list of models (or sub-collections) explored by the collection

control

store the list of user-defined model settings and optimization parameters

Active bindings

criteria

a data frame with the values of some criteria for the collection of models

loglik

not defined for a collection (which of its models?) – accessing it raises an informative error instead of silently returning `NULL`. Use `logLik()` for every model's log-likelihood, or `$get_best_model()$loglik` for a single one.

Methods


NormalBlockVarCollection$optimize()

optimizes every model (or sub-collection) in the collection

Usage

NormalBlockVarCollection$optimize(
  control = list(niter = 500, threshold = 1e-04, verbose = TRUE)
)

Arguments

control

optimization parameters (niter and threshold). When `control$clustering_init` is `"best_of_inits"`, each leaf model is fit via its own `best_of_inits()` instead of a plain `optimize()`.


NormalBlockVarCollection$print()

User-friendly print method: model type and the range of q/sparsity explored. See `summary()` for the full criteria table.

Usage

NormalBlockVarCollection$print()


NormalBlockVarCollection$summary()

Summarize the collection: model type, full criteria table, and the range of q/sparsity explored.

Usage

NormalBlockVarCollection$summary()

Returns

An object of class `summary.NormalBlockVarCollection`, printed with a dedicated [print.summary.NormalBlockVarCollection()] method.


NormalBlockVarCollection$clone()

The objects of this class are cloneable with this method.

Usage

NormalBlockVarCollection$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# An internal abstract base class, never instantiated directly -- see
# normal_block() for how collections (NormalBlockVarCollectionClusters,
# NormalBlockVarCollectionSparsity, NormalBlockVarCollectionClustersSparsity)
# are actually created and fitted.