2008-08-29  Jun Yan <jyan@stat.uconn.edu>

	* Bug fixed in the random number generation for the 
	Clayton copula.	

	* empcop*.test functions renamed to *indepTest.
	    
	* Documentation improved.

2008-07-17  Jun Yan <jyan@stat.uconn.edu>

	* Ivan has implemented and tested multiplier CLT 
	goodness-of-fit tests (bivariate and multivariate) for 
	certain copulas.

	* Restructured R files under directory R.

	* Expressions for derivatives of cdf/pdf are now stored 
	as opposed to computed on the fly.

	* Numerical approximation functions for tau and rho
	and its derivatives for special cases are now stored 
	in sysdata.rda under directory R.


2008-01-22  Ivan Kojadinovic  <ivan@stat.auckland.ac.nz>

	* The structure of the empcop*.test has been changed.
	All the statistics are computed using the same code.
	The only difference comes from the array J which changes 
	according to whether * in {u,m,s,sm}. The computation 
	is much faster.

2008-01-14  Jun Yan <jyan@stat.uconn.edu>

	* Restructured empcopsm for better performance. 
	Arrays W, K, and L are stored for reference in each permutation.
	The computation is about 3 times faster.
	
	* Fixed a bug in random permutation:
	(i + 1) * runif() instead of i * runif().
	The bug is seen for the case n = 2, where no permutation 
	would happen.
	
	* When compute p-values of Tippett, use obs <= sim as oppose to 
	obs < sim because this statistic is discrete.
	
2008-01-02  Ivan Kojadinovic  <ivan@stat.auckland.ac.nz>

	* The tests of independence based on the empirical copula 
	have been renamed to empcopu.test (univariate) and 
	empcopm.test (multivariate).

	* Some computations have been improved.

	* Serial analogs of these tests have been implemented. They 
	are called empcops.test and empcopsm.test and can be used to 
	test serial independence in univariate and multivariate 
	continuous time series.

2007-12-11  Jun Yan <jyan@stat.uconn.edu>

	* Fixed a bug in fitCopula (thanks to Rodrigo Dupleich
	<rodrigo.dupleich@citi.com> for reporting).	

2007-12-07  Ivan Kojadinovic  <ivan@stat.auckland.ac.nz>

	* Added the function empcop.rv.test, a test of independence 
	  among continuous random vectors based on the empirical copula.

	* Improved empcop.test.
	
	* Fixed a bug in fgm.c.

2007-10-16  Jun Yan  <jyan@stat.uconn.edu>

	* Added \encoding{latin1} in empcop.test.Rd.

	* Fixed warnings and notes issued by R (2.6.0) CMD check.

2007-08-26  Jun Yan  <jyan@stat.uconn.edu>

	* Added try-error handler for loglikCopula and loglikMvdc.
	This will allow the optimizer to keep searching when NaN is returned.

	* Changed the way to generate function calls to evaluate 
	[dpqr]<distrib> for each margin, thank to 
	Martin Maechler <maechler@stat.math.ethz.ch>.
	The package can interact now with package nor1mix.

2007-06-06  Jun Yan  <jyan@p-lnx401.stat.uiowa.edu>

	* Fixed random number generator of amhCopula.
	The formula in Johnson (1988) has undefined quantities.

2007-06-02  Ivan Kojadinovic  <ivan.kojadinovic@univ-nantes.fr>

	* Farlie-Gumbel-Morgenstern class implemented with
	distribution, density and random number generation. 
	Class needs to be properly tested, especially random 
	number generation.

2007-06-01  Jun Yan  <jyan@p-lnx401.stat.uiowa.edu>

	* Merged with package copulab by Ivan Kojadinovic 
	<ivan.kojadinovic@.univ-nantes.fr>, who
	provides the multivariate independence test of 
	Genest and Rmillard (2004).
	

2007-05-18  Jun Yan  <jyan@p-lnx401.stat.uiowa.edu>

	* Association measures are exported into the namespace:
	kendallsTau, spearmansRho, and tailIndex. Calibration
	functions are implemented for Kendall's tau and Spearman's rho. 

	* Extreme value copula class is implemented. This class 
	includes Galambos, Husler-Reiss.

	* Added Archimedean copula Ali-Mikhail-Haq.

	* Added Plackett copula.

2007-04-28  Jun Yan  <jyan@p-lnx401.stat.uiowa.edu>

	* The three Archemedean copulas (clayton, frank, and gumbel) now
	have their density expressions imported from mathematica, after 
	some symbolic simplification, which helps to eliminate some numerical
	precisions problems on the boundary of the unit square. 

	Frank copula has the most complicated expressions. On 4GB memory
	machine it ran out of memory for dim = 10. So for frank copula, the
	maximum dimension implemented is dim = 6.	
	
	The symbolic expressions are processed in R with function deriv
	to generate efficient algorithmic expressions.


