Changes from ver 1.0-5 to ver 1.0-6 [March-12-2019] 1) multiway-package * Added cpd = canonical polyadic decomposition (N-way) * Added examples to Tucker help files (Tucker1 and Tucker2). * Bug fix for tucker checks with fixed or starting weights. * Modified examples for parafac2 and sca help files. 2) cpd * Function for fitting N-way canonical polyadic decomposition. * This is an N-way generalization of the parafac function. 3) parafac2 * Modified the data generation code for help files. * No longer calls the sample function to generate data. 4) sca * Modified the data generation code for help files. * No longer calls the sample function to generate data. 5) tucker * Bug fix (checks with Fixed or Start weights) * Added Tucker2 and Tucker1 examples to help file Changes from ver 1.0-4 to ver 1.0-5 [June-10-2018] 1) multiway-package * Package file is now update-to-date with Description file * Changes in defaults of nscale (now uses root mean square of 1) * nrescale was removed (nscale has been preferred since ver 1.0-1) * Improvements to all of the rescaling and resigning functions * Updates to indscal function (similar to parafac and parafac2) * Added function mcr = multiway covariates regression * Now offers 24 possible constraints for parafac and parafac2 which are fit via the cmls function (in CMLS package) * Internal improvements for fitting parafac and parafac2 * Afixed, Astart, and Astruc arguments added for parafac * Changes to const.control, print.parafac, and print.parafac2 * Added *modes inputs to parafac and parafac2 2) const.control * No longer has argument "nonneg". Note that non-negativity is now controlled via "const" argument for smoothness constraints. * Added the argument "intercept". 3) const (from CMLS package) * Prints/returns the six letter constraint code and corresponding description. * Default prints all 24 possible constraint options. 4) indscal * Several new arguments added to reflect updates to parafac function. * Change in default functionality (non-negativity now imposed on C) * No longer allows for unconstrained Mode C update. 5) cmls (from CMLS package) * Function for constrained multivariate least squares. * Used for fitting constrained ALS algorithm in parafac and parafac2. 6) mcr * Function for fitting multiway covariates regression model. * Allows for constraints on the parameters (via cmls). 7) nscale * New default uses newscale, which is desired root-mean-square * Old input ssnew (sum-of-squares) is still allowed. 8) parafac * Now offers 24 possible constraints (see ?const) * Internal improvements for fitting (via cmls) * Added arguments Afixed, Astart, and Astruc * Added *modes arguments for specifying unimodality constraints 9) parafac2 * Now offers 24 possible constraints (see ?const) * Internal improvements for fitting (via cmls) * Added *modes arguments for specifying unimodality constraints 10) rescale and resign * Now checks to ensure new scale and sign are non-zero * Can handle degenerate solutions with a column of zeros in weights. Changes from ver 1.0-3 to ver 1.0-4 [Nov-13-2017] 1) multiway-package * Bug fix: parafac2 initialization with nfac = 1 * Missing data now allowed (as NA) and iteratively imputed - parafac, parafac2, and tucker * Added progress bar option ('verbose' argument) - parafac, parafac2, and tucker * Expanded functionality of ncenter for list arguments * Improved stability tolerance (mpinv and smpower) * Improved internal computations for corcondia * Improved initializations for parafac2 nesting Mode * Updated Helwig (2017) reference throughout. 2) corcondia * Improved computation for 'parafac' and 'parafac2' objects * CCD now calculated more efficiently for large 'nfac' 3) mpinv and smpower * Improved stability tolerance (now depends on data size) 4) parafac * Missing data now allowed (as NA) and iteratively imputed * Added progress bar option ('verbose' argument) * Updated reference to Helwig (2017) 5) parafac2 * Bug fix: now possible to fit model with nfac = 1 * Improved initializations for nesting mode weights * Missing data now allowed (as NA) and iteratively imputed * Added progress bar option ('verbose' argument) * Updated reference to Helwig (2017) 6) tucker * Missing data now allowed (as NA) and iteratively imputed * Added progress bar option ('verbose' argument) Changes from ver 1.0-2 to ver 1.0-3 [May-17-2017] 1) multiway-package * Bug fix: starting values and non-negativity constraints (parafac and parafac2) * Bug fix: when using rescale.sca with type="sca-ecp" * Reformatted the output for indscal (now more comparable to other outputs) * Reformatted the output for parafac2 (now x$A is list of Mode A weights) * Added unimodal, monotonic, periodic, and smoothness constraints to parafac and parafac2 * Added const.control argument to control new constraint options * Added print method for indscal, parafac, parafac2, sca, and tucker objects * Added sum of squared errors to output results (x$SSE) * Components are no longer ordered according to R^2 when using structure constraints * Added identifiability check on number of factors for tucker model * Improvements to internals of smpower function 2) const.control * New function to control the functional constraints (3-6) * Can adjust the degrees of freedom (df) for spline basis * Can adjust the polynomial degree (degree) for spline basis * Can constrain the function to be non-negative (nonneg) 3) indscal * Added print method (prints constraint, fit, and convergence information) * Added various items to output (to be comparable to other methods) * Added sum of squared errors to output results (x$SSE) * Removed x$strain output (because this is equal to x$SSE) 4) parafac * Bug fix: now possible to use starting values and non-negativity constraints on same mode * Added print method (prints constraint, fit, and convergence information) * Added sum of squared errors to output results (x$SSE) * New constraint option: const[j]=3 for unimodal constraint * New constraint option: const[j]=4 for monotonic constraint * New constraint option: const[j]=5 for periodic constraint * New constraint option: const[j]=6 for smoothness constraint * New constraint option: control argument can be used to control options for constraints 3-6 5) parafac2 * Change in formatting of output: - x$A is now a list of Mode A weights - x$Phi is the common crossproduct matrix for Mode A * Added print method (prints constraint, fit, and convergence information) * Added sum of squared errors to output results (x$SSE) * Bug fix: now possible to use starting values and non-negativity constraints on same mode * New constraint option: const[j]=3 for unimodal constraint * New constraint option: const[j]=4 for monotonic constraint * New constraint option: const[j]=5 for periodic constraint * New constraint option: const[j]=6 for smoothness constraint * New constraint option: control argument can be used to control options for constraints 3-6 6) sca * Bug fix: rescale.sca with type="sca-ecp" (fixed rescaling of Phi matrix) * Added print method (prints constraint, fit, and convergence information) * Added sum of squared errors to output results (x$SSE) 7) tucker * Added print method (prints constraint, fit, and convergence information) * Added identifiability constraint for 'nfac' input: need nfac[j] <= prod(nfac[-j]) * Added sum of squared errors to output results (x$SSE) Changes from ver 1.0-1 to ver 1.0-2 [Feb-19-2016] 1) multiway-package * Added "corcondia" function * Added "mpinv" function * Added "GCV" and "edf" to model outputs * Structure constraints for parafac and parafac2 * Improvements for nscale with list inputs 2) corcondia * New function to calculate Core Consistency Diagnostic * For examining fit of Parafac or Parafac2 models 3) mpinv * New function to calculate Moore-Penrose Pseudoinverse * Calculated via stabilized singular value decomposition 4) nscale * Changes in default functioning for lists * Now possible to scale data modes across or within lists 5) parafac and parafac2 * Can input structure matrix to constrain pattern of weights * Can constrain structure of Phi matrix for parafac2 6) parafac, parafac2, sca, and tucker * Generalized Cross-Validation (GCV) now reported * Effective degrees of freedom (edf) now reported Changes from ver 1.0-0 to ver 1.0-1 [Aug-26-2015] 1) multiway-package * Speed-ups for indscal, parafac, and parafac2 * congru: new function to calculate Tucker's congruence coefficient * Changes in convergence tolerance for all functions * Can now output all random starts (instead of only best) * Renamed function "nrescale" to "nscale" ("nrescale" still works) * Added "reorder" functionality for all methods * Added "rescale" functionality for all methods * Added "resign" functionality for all methods * Bug fixes for SCA-IND model with type="sca-ecp" * More customizability for parafac2 (fixed correlation structures) 2) congru * New function to calculate Tucker's congruence coefficient * Functionality is similar to cor and cov functions in R 3) indscal * Improvements to internals (speed-ups) * Now uses change in R^2 to determine ALS convergence * Default convergence tolerance now 10^-4 * Can now output all random starts (instead of only best) * Can use "reorder" to reorder factors of fit INDSCAL model * Can use "rescale" to rescale factors of fit INDSCAL model * Can use "resign" to resign factors of fit INDSCAL model 4) parafac * Improvements to internals (speed-ups) * Now uses change in R^2 to determine ALS convergence * Default convergence tolerance now 10^-4 * Can now output all random starts (instead of only best) * Can use "reorder" to reorder factors of fit Parafac model * Can use "rescale" to rescale factors of fit Parafac model * Can use "resign" to resign factors of fit Parafac model 5) parafac2 * Improvements to internals (speed-ups) * Now uses change in R^2 to determine ALS convergence * Default convergence tolerance now 10^-4 * Can now output all random starts (instead of only best) * Can use "reorder" to reorder factors of fit Parafac2 model * Can use "rescale" to rescale factors of fit Parafac2 model * Can use "resign" to resign factors of fit Parafac2 model * New inputs: Gfixed and Gstart * Default now randomly generates C weights from uniform[0,1] 6) sca * Improvements to internals (speed-ups) * Now uses change in R^2 to determine ALS convergence * Default convergence tolerance now 10^-4 * Can use "reorder" to reorder factors of fit SCA model * Can use "rescale" to rescale factors of fit SCA model * Can use "resign" to resign factors of fit SCA model * Bug fix for reporting of C weights with type="sca-ecp" 7) tucker * Now uses change in R^2 to determine ALS convergence * Default convergence tolerance now 10^-4 * Can now output all random starts (instead of only best) * Can use "reorder" to reorder factors of fit Tucker model * Can use "rescale" to rescale factors of fit Tucker model * Can use "resign" to resign factors of fit Tucker model