• The distribution argument now takes the return values of functions exact(), approximate() or asymptotic() as well. Those functions can be used to specify parameters, such as the number of Monte Carlo replications via ..., distribution = approximate(B = 9999), ....
• show() returns objects (of class "htest", for example) invisibly.
• expectation() returns a vector, not a matrix.
• New generic variance() for extracting the variance(s) of linear statistics.
• Only variances (instead of the whole covariance matrix) is computed when the distribution of maximum-type test statistics is to be _approximated_.
• data may be an object of class "exprSet" (-> Biobase), the vignette has an example.
• logrank_trafo() (and surv_test()) now have a ties.method argument, see ?surv_test for more information.