Package index • normalblockr

User-facing functions

Main entry points for fitting a Normal-Block model and simulating data

normal_block(): Normal-block model
NB_control(): NB_control
generate_normal_block_var_data(): Generate Normal Block Data

Model and data classes

R6 classes returned by normal_block(). NormalBlockData wraps the responses and design matrix; NormalBlockVarClusters (optionally ZI-prefixed) are single fitted models, known- or unknown-clustering; NormalBlockVarCollection are collections of models explored over a range of q and/or sparsity penalties.

NormalBlockData: Data Container for Normal-Block Models
NormalBlockVarKnownClusters: Normal-Block Model with Known Clustering
NormalBlockVarUnknownClusters: Normal-Block Model with Unknown Clustering
ZINormalBlockVarKnownClusters: Zero-Inflated Normal-Block Model with Known Clustering
ZINormalBlockVarUnknownClusters: Zero-Inflated Normal-Block Model with Unknown Clustering
NormalBlockVarCollectionClusters: Collection of Normal-Block Models over a Range of Cluster Counts
NormalBlockVarCollectionSparsity: Collection of Normal-Block Models over a Sparsity Path
NormalBlockVarCollectionClustersSparsity: Collection of Normal-Block Models over Cluster Counts and Sparsity Levels

Data sets

brca_rppa: Breast cancer proteomics data (TCGA, RPPA)
onema: French stream fish community data (ONEMA / OFB electrofishing surveys)
university: University webpages text data (CMU "4 Universities" / WebKB)

S3 methods

Standard extractors and methods for a fitted model (any NormalBlockVarBase subclass) and for a collection of models (any NormalBlockVarCollection subclass)

coef(<NormalBlockVarBase>): Extract Model Coefficients
fitted(<NormalBlockVarBase>): Extract Fitted Values
predict(<NormalBlockVarBase>): Predict Method for Normal-Block Models
sigma(<NormalBlockVarBase>): Extract the Latent-Block Covariance Matrix
print(<NormalBlockVarBase>): Print a Normal-Block Model
summary(<NormalBlockVarBase>): Summarize a Normal-Block Model
print(<summary.NormalBlockVarBase>): Print a Normal-Block Model Summary
plot(<NormalBlockVarBase>): Plot a Normal-Block Model
logLik(<NormalBlockVarBase>): Extract Log-Likelihood of a Normal-Block Model
BIC(<NormalBlockVarBase>): Bayesian Information Criterion for a Normal-Block Model
print(<NormalBlockVarCollection>): Print a Collection of Normal-Block Models
summary(<NormalBlockVarCollection>): Summarize a Collection of Normal-Block Models
print(<summary.NormalBlockVarCollection>): Print a Collection Summary
logLik(<NormalBlockVarCollection>): Extract Log-Likelihood of a Collection of Normal-Block Models
BIC(<NormalBlockVarCollection>): Bayesian Information Criterion for a Collection of Normal-Block Models

Internal

Abstract base classes, low-level helpers and exploratory code kept for reference; not part of the user-facing API

NormalBlockVarBase: Base Class for Normal-Block Models
NormalBlockVarCollection: Base Class for a Collection of Normal-Block Models
SelectionNClusters: Select the Number of Clusters by Split/Merge Search
get_model(): Create a Normal-Block Model Object
isNB(): Check if an Object is a Normal-Block Model