*   Minor change
**  Major change

3.0-2
        *  Fixed bug involving mismatch between group.multiplier and group if
	   group is given out of order.
	*  'Lung' and 'Birthwt' data sets now use factor representation of
	   group, as character vectors are inherently ambiguous with respect to
	   order.

3.0-1
        *  Fixed memory allocation bug
	*  Re-introduced 'birthwt.grpreg' for backwards compatibility, but this
	   is deprecated.

3.0-0
	** Added methods for survival analysis (Cox modeling): grpsurv,
	   cv.grpsurv, AUC, predict.grpsurv
	*  Added vignettes (a quick-start guide and a detailed description of
	   available penalties)
	*  Added option to return fitted values from cross-validation folds
           (returnY=TRUE) to cv.grpreg and cv.grpsurv
	*  Reformatted (and renamed) example data set 'Birthwt'; added example
	   data set 'Lung' for survival
	*  Added user interrupt checking
	*  Greatly expanded suite of tests; various bugs identified and fixed
	   as a result

2.8-1
	*  Fixed bug for predict.grpreg(fit, type="nvars") or 
	   type="ngroups" when scalar lambda value is passed
	*  cv.grpreg now allows user to specify lambda (thanks to Vincent
	   Arel-Bundock for suggesting this change)
	*  Updated citations

2.8-0
	** More flexible interface through the 'group' argument:
           groups may now be out of order, and may be named rather
           than only consecutive integers
	*  Fixed bug for multitask learning when number of outcomes = 2
           (thank you to Aluma Dembo for pointing this out)
	*  Cross-validation for multitask learning now respects the
           multivariate structure of the response matrix
	*  summary.cv.grpreg now describes multitask learning models
           more accurately
	*  Fixed bug in cv.grpreg when attempting to use leave-one-out
	   cross-validation
	*  'X' can now be a matrix of integers (previously this would
           result in the passing of an incompatible storage type to C)
	*  Additional error checks to prevent cryptic error messages
	*  Internal modifications to convergence monitoring
	*  Added corrected AIC and extended BIC as options with select()

2.7-1
	*  More rigorous initialization at C level to prevent possible 
	   memory access problems
	*  Fixed predict() for types 'vars', 'nvars', and 'ngroups' with
	   multivariate outcomes
	*  As a consequence, summary(cvfit) now works for multivariate
	   outcomes (thank you to Cajo ter Braak for pointing out that
	   that this was broken)

2.7-0
	*  Internal restructuring: .Call now used instead of .C
	*  Added support for Poisson regression
	*  Fixed bug in cv.grpreg when attempting to use leave-one-out
	   cross-validation (thank you to Cajo ter Braak for pointing this
	   out)

2.6-0
	** Various internal changes to make the package more efficient for
	   large data sets

2.5-0
	** Added group exponential lasso method.
	*  Added gmax option
	*  Added nvars and ngroups option to predict
	*  Modified appearance of summary.cv.grpreg display.

2.4-0
	** Added options in plot.cv.grpreg to plot estimates of r-squared,
	   signal-to-noise ratio, scale parameter, and prediction error in
	   addition to cross-validation error (deviance)
	** grpreg and cv.grpreg now allow matrix y to facilitation group
	   penalized methods for seemingly unrelated regressions/multitask
	   learning.  This is something of a 'beta' release at this point,
	   and will be developed and refined further in future releases.
	*  Added summary method for cv.grpreg objects
	*  Added coef and predict methods for cv.grpreg objects
	*  Fixed bug in predict type='coefficients' when 'lambda'
	   argument specified.
	*  Brought gBridge up to date so that it now handles constant
	   columns, etc. (see 2.2-0)
	*  Fixed bug in cv.grpreg with user-defined lambda values.

2.3-0
	*  Switched to SVD-based orthogonalization to allow for linear
	   dependency within groups

2.2-1
	*  Fixed compilation error for 32-bit Windows
	*  Fixed bug in calculation of binomial deviance when fitted
	   probabilities close to 0 or 1 arise

2.2-0 
        *  cv.grpreg: Now returns full data fit as well as CV errors
        *  The above thereby allows cv.grpreg to handle constant columns,
	   and fixes some bugs
        *  select: Now allows ... options to be passed to logLik
	*  plot: Added option to plot norm of each group, rather than
	   individual coefficients
	*  predict: "vars", "groups", and "norm" options added
	*  logLik: fixed bug -- no longer calculates (meaningless)
	   log-likelihoods for saturated models (thank you to Xiaowei Ren 
	   for pointing this out)
	*  fixed bug for returning group when some groups were eliminated
	   due to constant columns

2.1-0
	*  Fixed bug involving orthogonalization with unpenalized groups
        *  grpreg can now handle constant columns (they produce beta=0)
	*  Internal restructuring of C code

2.0-0
	** New algorithm for group lasso
	** (L2) Group MCP, group SCAD methods added
	** Added cv.grpreg to facilitate cross-validation
	*  Extensive internal refactoring of code
	*  Added dfmax option
	*  Added group.multiplier option
	*  Allows specification of unpenalized groups
	*  standardize and orthogonalize functions added
	*  gBridge now divorced from grpreg and given separate function
	*  Much more extensive and reproducible code testing

1.2-0
	*  DESCRIPTION: Fixed contact info
	*  CITATION: Updated citation
	*  grpreg: Removed 'monitor' option
	*  grpreg: Changed 'n.lambda' to 'nlambda'
	*  grpreg: Changed 'a' to 'gamma' for MCP tuning parameter
	*  grpreg: Changed 'lambda2' to 'alpha'
	*  grpreg: Added 'loss' to value returned
	** grpreg.c: Fixed bug in calculation of df for gLasso
	*  logLik: Added logLik method
	** select: Syntax modified (no longer requires X, y to be passed)
        *  criteria: Obsolete, removed
	** plot.grpreg: Made plotting function more flexible
