Package index • muscal

All functions

aligned_interbattery(): Aligned Interbattery Analysis
aligned_mcca(): Aligned Multiblock Canonical Correlation Analysis (Aligned MCCA)
aligned_mfa(): Aligned Multiple Factor Analysis (Aligned MFA)
aligned_rrr(): Aligned Reduced-Rank Regression
alignment_coverage(): Report Reference-Feature Alignment Coverage
anchored_mcca(): Anchored Multiblock Canonical Correlation Analysis (Anchored MCCA)
as_multifer_adapter(): Resolve a muscal fit to a multifer adapter
autoplot(<bada>): Autoplot for BaDA
autoplot(<bamfa>): Autoplot for BaMFA
autoplot(<covstatis>): Autoplot for COVSTATIS
autoplot(<linked_mfa>): Autoplot for Linked MFA
autoplot(<mfa>): Autoplot for MFA
autoplot(<penalized_mfa>): Autoplot for Penalized MFA
bada() bootstrap(<bada>) reprocess(<bada>) project(<bada>): Barycentric Discriminant Analysis (generic)
bamfa(): Barycentric Multiple Factor Analysis (BaMFA)
bilinear_mixed(): Bilinear Repeated-Measures Mixed Model
bilinear_mixed_easy(): Easy Front-End for Bilinear Mixed
bilinear_mixed_recommend(): Recommend Practical Defaults for Bilinear Mixed
bilinear_mixed_tune(): Tune Bilinear Mixed Hyperparameters via Subject-Block CV
block_source() as_block_source() read_block(): Out-of-Core Block Sources
check_duality(): Verify duality between ROI- and RV-space coordinates
components(<design_mfa>): Summarize Components for a Design-MFA Effect
coordinate_feature_map(): Build a Sparse Coordinate-to-Feature Map
coordinate_feature_maps(): Build Coordinate Maps for Several Subjects
coupled_graph_anchored_mfa(): Coupled Graph-Anchored Multiple Factor Analysis
covstatis(): STATIS for Covariance Matrices (generic)
cv_muscal(): Cross-Validate Muscal Models with Multidesign Folds
default_metrics(): Default Metrics for a Muscal Task
design_mfa(): Effect-Specific Multilevel Components for Trialwise Fields
design_mfa_control(): Control Numerical Design-MFA Calculations
design_mfa_example_data(): Construct a Small Deterministic Design-MFA Example
distatis(): DISTATIS for Multiple Distance Matrices
effect_map(): Extract One Effect Loading Map
effect_scores() effect_loadings(): Extract Effect Scores or Spatial Loadings
effects(<design_mfa>): Extract Design Effects from a Design-MFA Fit
estimability(): Report Design-MFA Estimability
estimate_components() loading_reliability(): Estimate the number of components and loading reliability (shared helpers)
graph_anchored_mfa(): Graph-Anchored Multiple Factor Analysis
infer_aligned_rrr(): Multifer Inference for Aligned RRR
infer_bada(): Multifer Inference for BaDA
infer_covstatis(): Multifer Component Tests for COVSTATIS
infer_design_mfa(): Subject-Level Inference for a Design-MFA Effect
infer_muscal(): Standard Resampling and Inference for Muscal Fits
ipca(): Integrated Principal Components Analysis (generic)
ipca_tune_alpha(): Tune Tied Penalties for iPCA via 1D Alpha Search
anchored_mfa() linked_mfa(): Anchored Multiple Factor Analysis (Anchored MFA)
mcca(): Multiblock Canonical Correlation Analysis (generic)
metric_registry(): Metric Registry for Muscal Tasks
mfa-plots: Plotting Functions for MFA and Linked MFA
mfa(): Multiple Factor Analysis (generic)
nested_tune_design_mfa(): Nested Held-Out-Subject Evaluation for Design-MFA Tuning
orient_components(): Orient Component Signs for Fitted muscal Models
penalized_mfa(): Penalized Multiple Factor Analysis (MFA)
penalized_mfa_clusterwise() pmfa_cluster(): Penalized MFA with Clusterwise Spatial Smoothness Constraints
performance_metrics(): Compute Task-Aware Performance Metrics
plot(<bada>): Plot BaDA Results
plot(<bamfa>): Plot BaMFA Results
plot(<covstatis>): Plot COVSTATIS Results
plot(<design_mfa>): Plot a Design-Effect Component Trajectory
plot(<distatis>) autoplot(<distatis>) plot_partial_scores(<distatis>) plot_block_weights(<distatis>) plot_block_similarity(<distatis>): Plot DISTATIS Object and Assessor Maps
plot(<linked_mfa>): Plot Linked MFA Scores
plot(<mfa>): Plot MFA Scores
plot(<penalized_mfa>): Plot Penalized MFA Results
plot_barycenters(): Plot Class Barycenters for BaDA
plot_block_fit(): Plot Block Reconstruction Error
plot_block_similarity(): Plot Block Similarity Matrix
plot_block_weights(): Plot Block Weights
plot_convergence(): Plot Convergence Trace
plot_coverage(): Plot Block Coverage Map
plot_feature_groups(): Plot Feature Group Loadings
plot_global_local(): Plot Global vs Local Decomposition for BaMFA
plot_loading_alignment(): Plot Loading Alignment for Penalized MFA
plot_loadings(): Plot Variable Loadings
plot_partial_scores(): Plot Partial Factor Scores
plot_subjects(): Plot subject scores in RV space
plot_variance() plot_variance.covstatis() plot_variance.bada() plot_variance.penalized_mfa(): Plot Variance Explained (Scree Plot)
plot_variance.distatis(): DISTATIS Inertia Plot
predict(<aligned_interbattery>): Predict from an Aligned Interbattery Fit
predict(<aligned_mfa>): Predict from an Aligned MFA Fit
predict(<aligned_rrr>): Predict from an Aligned RRR Fit
predict(<anchored_mfa>): Predict from an Anchored MFA Fit
predict(<bamfa>): Predict method for BaMFA objects
predict(<coupled_graph_anchored_mfa>): Predict from a Coupled Graph-Anchored MFA Fit
predict(<design_mfa>): Predict Group-Average Activation Fields
predict(<graph_anchored_mfa>): Predict from a Graph-Anchored MFA Fit
predict(<ipca>): Predict from an iPCA Fit
predict(<mcca>): Predict from an MCCA Fit
predict(<mfa>): Predict from a Multiple Factor Analysis Fit
predict(<penalized_mfa_clusterwise>): Predict Clusterwise Penalized MFA Scores or Reconstructions
predict(<response_aligned_mfa>): Predict from a Response-Aligned MFA Fit
print(<bamfa>): Print Method for BaMFA Objects
print(<penalized_mfa>): Print Method for Penalized MFA Objects
print(<penalized_mfa_clusterwise>): Print Method for Penalized MFA Clusterwise Objects
project() reprocess(): Re‑export selected generics from **multivarious**
project(<aligned_interbattery>): Project New Rows into an Aligned Interbattery Space
project(<aligned_mfa>): Project New Rows into an Aligned MFA Space
project(<aligned_rrr>): Project New Rows into an Aligned RRR Space
project(<anchored_mfa>): Project New Rows into an Anchored MFA Space
project(<coupled_graph_anchored_mfa>): Project New Rows into a Coupled Graph-Anchored MFA Space
project(<design_mfa_effect>): Project New Fields onto a Design-Effect Basis
project(<graph_anchored_mfa>): Project New Rows into a Graph-Anchored MFA Space
project(<penalized_mfa_clusterwise>): Project Clusterwise Penalized MFA Observations
project(<response_aligned_mfa>): Project New Rows into a Response-Aligned MFA Space
project_cov(): Project a Covariance Matrix (generic)
project_covariate() project_table_covariate() project_feature_covariate(): Project a Table- or Feature-Level Covariate (generic)
project_covariate(<distatis>): Project Covariates onto DISTATIS Maps
project_distance() project(<distatis>) project_cov(<distatis>): Project a Supplementary Assessor's Distances
project_subjects(): Project and Summarize New Subject Data (generic)
project_subjects(<distatis>): Supplementary Assessor Maps and Diagnostics for DISTATIS
reconstruct(<covstatis>): Low-rank reconstruction of the compromise matrix
reconstruct(<distatis>): Reconstruct the Normalized DISTATIS Compromise
reconstruct(<mfa>) reconstruct_new(<mfa>): Reconstruct Data from an MFA Fit
response_aligned_mfa(): Response-Aligned Multiple Factor Analysis
roi_map(): Extract ROI map for a compromise dimension
scores(<distatis>) sdev(<distatis>): Scores from a DISTATIS Model
significant_components(): Identify Significant Components via RMT and Inter-block Coherence Tests
sorting_distances(): Convert Sorting Partitions to Distance Matrices
subject_effects(): Extract Subject-Specific Design Effects
synthetic_multiblock(): Generate synthetic multiblock data
tune_design_mfa(): Tune Design-MFA Components with Held-Out Subjects