Changes to version 0.6-2 (14 September 2015):
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- lgarch:

* Formula for the variance-covariance matrix of the ARMA-representation corrected when method="ls"

* improved column-names handling of X-regressors

* the dates/index of regressor(s), i.e. the xreg argument, is automatically matched with dates/index of the regressand

Main changes to version 0.5 (1 September 2014):
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- lgarchSim: c.code argument added with default TRUE (i.e. compiled C-code is used for the recursion; this speeds up simulations considerably)

- S3 method summary added for lgarch and mlgarch objects

- lgarch, mlgarch: backcast.values argument removed

- lgarchRecursion1: for improved numerical stability the backcast values of ln(y^2) was changed to the empirical mean. Also, a bug that occurred whenever c.code=FALSE was corrected

Main changes to version 0.4 (1 July 2014):
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- lgarch:

* mean-correction as estimation-option added

- a third estimation method was added: QML via the centred Chi-squared distribution as instrumental density

- fitted.lgarch: bug fix (the bug induced incorrect fitted values at zero-locations)

- stylistic changes to the documentation

Main changes to version 0.3 (1 June 2014):
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- functions and S3 methods for the simulation and estimation of the multivariate CCC-log-GARCH(1,1) model were added

- gdiff function added

- rss.lgarch function changed name to rss

- zoo-related bug corrected in glag 

- glag function: improved further, and the pad argument in the glag function acquired a new default (TRUE)

- minor improvements throughout, and several stylistic changes made to the documentation


Main changes to version 0.2 (28 April 2014):
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- lgarch function: A couple of bugs corrected in the parameter-indexing, which ocurred whenever the garch order argument was set to 0

- glag: Completely rewritten. Now it can also lag matrices, and it gives a "special treatment" to zoo-objects (the indexing is retained)

- function lgarchLogl changed name to lgarchObjective

- argument logl.penalty in lgarch function changed to objective.penalty

- lgarch function: the argument method=c("ml","ls") was added. If method="ml", then estimation is with Gaussian QML via the ARMA representation. If method="ls", then estimation is with least squares via the ARMA representation. Although asymptotically equivalent in most respects, the latter is slightly faster since one parameter less is estimated

- function rss.lgarch added (extract Residual Sum of Squares of ARMA representation) from an lgarch object

- function mlgarchSim added (simulate from a multivariate log-GARCH(1,1))

- function rmnorm added (generate from multivariate normal)

Version 0.1 (18 March 2014):
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- All versions until 1.0 should be considered as Beta-versions