propagate 1.0-3 (28-02-2014)
* As the new parametrization of 'dgnorm' tended to give convergence problems (bug kindly provided by Tony C), it was included into those distributions that are initially fitted by a grid of possible starting parameters in 'fitDistr'.
* The 'optim' function of 'fitDistr' was replaced by 'nls.lm' of the "minpack" package because it is more robust in terms of minimizing residal sum-of-squares.
* Updated 'Examples' section of 'bigcor'.
propagate 1.0-2 (27-01-2014)
* Modified 'rmises', 'rctrap' and 'rgtrap' so that a result vector is preallocated, which makes the three functions a bit faster, roughly 300000-400000 random numbers/second (3 GHz Pentium Dual Core).
* 'colVars' and 'rowVars' are now coded in C++ using the Rcpp framework. For a row-wise calculation of variances from a matrix of 500000 rows/10 columns this takes now only 100 ms!
* Added function 'bigcor' for creating VERY large correlation/covariance matrices, using a step-wise submatrix filling approach (Huh?). There is a corresponding blog entry to be found under http://rmazing.wordpress.com/2013/02/22/bigcor-large-correlation-matrices-in-r/.
* Generalized normal distribution 'dgnorm' now has a different parametrization that tallies with 'rgnorm' (bug kindly provided by Tony C).
propagate 1.0-1 (29-08-2013)
* First version and hence no update.