       

           RELEASE HISTORY OF THE "corpcor" PACKAGE


Version 1.6.9
- fixed a bug that made it possible that in very rare cases the shrinkage 
  intensity can become negative
- DOIs for all references added


Version 1.6.8
- import statements added required by R-devel


Version 1.6.7
- change of maintainer email address


Version 1.6.6
- is.positive.definite() and make.positive.definite() now use eigen()
  with option symmetric=TRUE, so that it works under R 3.0.0
  (thanks to Roberto Ugoccioni for reporting this issue)
            

Version 1.6.5
- License file removed
- Dependencies updated


Version 1.6.4
- estimate.lambda() now also works if the input data matrix has 
  two columns (thanks to Manuela Hummel for reporting this bug)


Version 1.6.3
- substantially faster estimate.lambda() for small sample size 
  and large dimensions (new algorithm suggested by Miika Ahdesm\"aki) 


Version 1.6.2
- new public functions estimate.lambda() and estimate.lambda.var()
  returning the shrinkage intensities for correlation and variance shrinkage
- some internal code reorganization


Version 1.6.1
- NAMESPACE file added
- small changes in de documentation


Version 1.6.0
- collapse option removed from:
  powcor.shrink, cor.shrink, invcor.shrink, cov.shrink, invcov.shrink
- default minimum R version changed to 2.10.0
- new function crossprod.powcor.shrink() to efficiently compute 
  R_shrink^alpha y without the need to explicitly compute R_shrink^alpha


Version 1.5.7
- the function mvr.shrink() has been removed (for a related function see the 
  "care" R package).
- mpower() now keeps row and column names.


Version 1.5.6
- cor.shrink() now also works if the input data matrix only has a 
  single column.


Version 1.5.5
- a numerical problem with symmetry check in invcor.shrink() and related
  functions has been resolved (thanks to Gad Abraham).
- following an idea by Miika Ahdesm\"aki the procedures for estimating the
  shrinkage intensities have been rewritten in pure R without employing
  any C code any more (w/o speed penalty!). 


Version 1.5.4
- mpower() now has an option to exclude nonzero eigenvalues
  and also checks whether the input matrix is symmetric.


Version 1.5.3
- small corrections to pass checks for R version 2.10.
- reference to Zuber and Strimmer (2009) added.


Version 1.5.2
- small corrections in the help pages, to pass the more stringent
  checks on .Rd files introduced in R in January 2009.


Version 1.5.1
- powcor.shrink() now collapses the identity matrix if alpha=0 and collapse=TRUE.
- help page for powcor.shrink was revised.
- package description was also revised.


Version 1.5.0
- new function powcor.shrink()  computes (very efficiently!) an arbitrary 
  power of the correlation shrinkage matrix (i.e.  R_shrink^alpha).
- invcor.shrink() is now a special case powcor.shrink() with alpha=-1.
- invcov.shrink() now also uses powcor.shrink().
- new mpower() utility function to estimate the matrix power
  of a real symmetric matrix.


Version 1.4.8
- new "collapse" option in cor.shrink, cov.shrink, invcor.shrink, invov.shrink
  to allow memory savings when lambda equals 1.
- to simplify code base two rarely used options were removed:
  "protect" and  "scale.by" (wt.scale is now always done using "sd").
- package depends now on R 2.7.0.
- documentation was polished.


Version 1.4.7
- change of license from "GPL 2 or later", to "GPL 3 or later".


Version 1.4.6
- following a suggestion (and a patch) by Nicola Soranzo internal big 
  objects are now explicitly removed when they are not needed anymore.  
  As a result, the package now needs less computer memory, and
  larger (partial) correlation matrices can be computed.


Version 1.4.5
- when partial correlations are computed using pcor.shrink() the
  returned matrix now has the standardized partial variances (i.e. 
  PVAR/VAR) attached under the attribute "spv".
- updated references in the help pages


Version 1.4.4
- the function wt.scale() is now *much* faster, especially for large p,
  due to using colSums() rather than apply() .. note that this indirectly 
  speeds up most other functions in the corpcor package!
- typos in the documtation were corrected and references updated


Version 1.4.3
- the shrinkage target for the variance is now the median (previously,
  variances were shrunken towards the mean).
- var.shrink now also has a"protect" argument. 
- limited translation shrinkage is now turned off by default 
   (i.e. protect has value zero). 
  

Version 1.4.2
- limited translation estimator implemented for the shrinkage estimate
  of the correlation matrix. This prevents excessive component risk.
- new functions for decomposing the covariance matrix and
  its inverse: decompose.cov(), decompose.invcov(), rebuild.invcov()
- new function pvar.shrink() to estimate partial variance.
- in the documentation the definition of partial variance and 
  partial covariance are corrected (following Whittaker 1990)  
- the functions cov2pcov(), pcov2cov(), pcov.shrink() have been removed.
- functions sm2vec(), vec2sm(), sm.index() back (from GeneTS)
- is.positive.definite() checks for complex eigenvalues.


Version 1.4.1:
- fast.svd() now doesn't use any more the LAPACK routines DGESVD
  to compute the singular value decomposition (this routine is deprecated
  from R version 2.3.0)
- weighted.var(), weighted.moments(), weighted.scale() are
  now called wt.var(), wt.moments(), wt.scale() 


Version 1.4.0:
- New functions mvr.shrink() and mvr.predict() for multivariate
  shrinkage regression.
- All shrinkage estimate now carry the class attribute "shrinkage.
  This allows for a more informative output via print.shrinkage()
- Removed functions:  sm2vec(), vec2sm(), sm.indexes()


Version 1.3.1:
- This versions fixes a bug present in "corpcor" version 1.3.0 
  and 1.2.0 but not in earlier versions.  This bug leads to a 
  (probably negligible) small bias in the computation of the 
  optimal shrinkage intensity. 
- The functions cov.bagged(), cor.bagged(), and pcor.bagged()
  have been removed.
- Typographical errors in the documentation were corrected.


Version 1.3.0:
- New function "var.shrink" to compute shrinkage estimates of 
  variances (target: average empirical variances.
- cov.shrink() and pcov.shrink() are now also based on shrunken 
  variances.
- Estimation of shrinkage intensities are now done in C.
  This greatly decreases the computational costs.
- Options "check.eigenvalues" and "exact.inversion" have been 
  removed in cor2pcor() and pcor2cor()
- The functions have been modified so that data sets with 
  zero-variance variables may also be analyzed (these will be in 
  effect ignored in estimating correlation but taken into account
  when estimating variances).


Version 1.2.0:
- Greatly reduced memory and faster computations.
- New code on fast inversion using Woodbury identity.
- Consequently, pcor.shrink() is now much faster .
- New functions for computation of weighted variances,
  weighted moments, and weighted rescaling.
- All covariance etc. estimators now also have the option to
  supply data weights".
- varcov() function removed (not necessary any more).
- Several parts of documentation updated.
- Juliane's Web address updated.


Version 1.1.2:
- Minor typos in documentation corrected.
- From this version is.positive.definite() works with
  arbitrary matrix (previously it required symmetric matrix).

  
Version 1.1.1:
- Reference to shrinkage covariance paper is updated.


Version 1.1:
- cor.shrink() is now the central estimator, and cov.shrink
  is derived.


Version 1.0:
- First stand-alone release (20 August 2005).
  This package contains various functions shrinkage estimation
  of (partial) correlation and covariance.
  Prior to release in this package the functions were part
  of the GeneTS package.

