implemented: a Fourier based approach (Shimotsu (2007) <10.1016/j.jeconom.2006.01.003>) and a wavelet based
approach (Achard and Gannaz (2016) <10.1111/jtsa.12170>).

implemented: a Fourier based approach (Shimotsu (2007) <doi:10.1016/j.jeconom.2006.01.003>) and a wavelet based
approach (Achard and Gannaz (2016) <doi:10.1111/jtsa.12170>).

Title: Component Models for Multi-Way Data
Description: Fits multi-way component models via alternating least squares algorithms with optional constraints (orthogonality and non-negativity). Fit models include Individual Differences Scaling, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

Description: Fits multi-way component models via alternating least squares algorithms with optional constraints (orthogonality, non-negativity, and structural). Fit models include Individual Differences Scaling, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

Description: Fits multi-way component models via alternating least squares algorithms with optional constraints: orthogonal, non-negative, unimodal, monotonic, periodic, smooth, or structure. Fit models include Individual Differences Scaling, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

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

Description: 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.

Title: Multi-way standard error clustering
Author: Nathaniel Graham and Mahmood Arai
Description: This package exports one function cluster.vcov, which implements
multi-way clustering using the method suggested by Cameron, Gelbach, &
Miller (2011).  Normal one and two-way clustering matches the results of
other common statistical packages.  Missing values are handled
transparently and rudimentary parallelization support is provided.