NOTE v1.2.1 is not backward compatible with earlier versions

Changes:

A new argument 'vars.mle' in 'tca' which controls the method used for optimization; setting to FALSE allows a much faster optimization.
A new argument 'fast_mode' in 'tcareg' allows a much faster optimization.
A new argument 'constrain_mu' in 'tca' allows to determine whether to constrain the mean parameters in the optimization; setting to false now allows to obtain p-values for the covariates in 'C1' and 'C2'.
A new 'scale' argument in 'tensor' for dividing estimates by estimated standard deviations.
Default values of several arguments have been changed.
Switched the default FDR method used in ‘tcareg’ back from “BY” to “BH” (can be changed by editing the config file).

TCA v1.1.0 (Release date: 11-14-2019)

Changes:

Introducing the argument 'C1.map' in the function 'tca' for allowing source-specific covariates 'C1' to affect only a user-defined subset of the sources.
Now allowing to provide 'tau' as an input to the 'tca' function.
Switched the FDR method used in 'tcareg' from "BH" to "BY".
Added a 'verbose' argument to all functions.

Bug fixes:

Added glmnet as a required dependency to the description file.
Fixed a formatting error in 'tcareg' in some cases where both 'C1' and 'C3' were used.
Fixed a problem in 'tca' in cases where 'refit_W=TRUE', 'C1=NULL', 'C2=NULL'.
Fixed logging issue in cases where 'debug=TRUE', 'refit_W=TRUE'.
Fixed a bug in the calculation of the returned value of 'tensor' in cases where 'C2' were provided.

TCA v1.0.0 (Release date: 05-22-2019)