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multiway

Component Models for Multi-Way Data

Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

Functions (26)

United States Alcohol Consumption Data (1970-2013)

Tucker's Congruence Coefficient

const.control

Auxiliary for Controlling Multi-Way Constraints

Core Consistency Diagnostic

cpd

N-way Canonical Polyadic Decomposition

Extract Multi-Way Fitted Values

Fast Non-Negative Least Squares

Individual Differences Scaling

Khatri-Rao Product

mcr

Multiway Covariates Regression

Mean Square of Given Object

Moore-Penrose Pseudoinverse

multiway-internal

Internal Multi-Way Functions

multiway-package

Component Models for Multi-Way Data

Center n-th Dimension of Array

Scale n-th Dimension of Array

Parallel Factor Analysis-1

Parallel Factor Analysis-2

Print Multi-Way Model Results

Reorder Multi-Way Factors

Rescales Multi-Way Factors

Resigns Multi-Way Factors

sca

Simultaneous Component Analysis

Symmetric Matrix Power

Sum-of-Squares of Given Object

Tucker Factor Analysis

multiway

Component Models for Multi-Way Data

v1.0-6

GPL (>= 2)

Authors

Nathaniel E. Helwig <helwig@umn.edu>

Initial release

2019-03-12

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