LOG of the CHANGES in the package tensorBSS

Version 0.3.9:
* Fixed a bug in "tPCAaug" which might have caused problems when using the quantile method to estimate the noise variance.
* Updated some references.

Version 0.3.8:
* Added the option "normalize" to functions mModeCovariance and mModeAutoCovariance that allows bypassing the normalization with the product of auxiliary mode sizes.
* Added the function "mFlatten".
* Added function "tPCAaug" and the corresponding printing function.
* Udpated some references.
* Una Radojicic became a contributor.
* Added the function "ggtaugplot".
* Added the arguments "position" and "scales" to the function "ggtladleplot".

Version 0.3.7:
* Made the use of the suggested package stochvol conditional in the examples of plot.tbss.Rd and tGFOBI.Rd.
* Added the package fICA as a suggested package.

Version 0.3.6:
* Removed from the list of suggested packages the now-deprecated package ElemStatLearn, in which the data set zip.train used in several of the package examples could be found
* Added the data sets zip.train and zip.test (originally in ElemStatLearn) to the package
* Added the function zip2image (originally in ElemStatLearn) to the package

Version 0.3.5:
* Added the functions tTUCKER(), tPCAladle(), tensorTransform2(), tensorBoot(), print.tladle() and ggtladleplot()
* Added Christoph Koesner as an author
* Changed list initialization from list() to vector("list", r)
* Added a remark to tensorVectorize.Rd that it returns a "transposed" data matrix
* Modified tensorCentering() and tensorStandardizing() to accept also user-specified location and scatters to be used for standardization

Version 0.3.4:
* Added tPP() for running tensorial projection pursuit
* Added the option k = 0 to k_tJADE() for not unmixing a mode at all
* Changed the maintainer email address
* Updated references

Version 0.3.3:
* Added k_tJADE() for computing the faster "k"-version of TJADE
* Updated references
* Updated the examples of tFOBI(), tJADE(), tSOBI(), tgFOBI() and tgJADE() to use tMD()

Version 0.3.2:
* Added tSIR() for computing sliced inverse regression estimators for tensor data

Version 0.3.1:
* Added an option to use a normed TFOBI matrix to tFOBI()
* Added a function tMD() for computing the MD-index of a Kronecker product of unmixing/mixing matrices
* Updated the example of tNSS.SD()
* Updated references

Version 0.3:
* Added the functions tNSS.SD(), tNSS.JD() and tNSS.TD.JD()
* Added the parameter k to the function tJADERotate() to be ready for the inclusion of tkJADE in a later update

Version 0.2:
* Added the function tPCA()

Version 0.1:
* First version submitted to CRAN

