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
