2016-05-22 Yang Feng <yang.feng@columbia.edu> Version 1.0
	*format the codes
	*implement the adaptive split scheme, by dividing the alphalist into three regions
	*change the custom method, into using all class 0 samples for determine the cutoff
	*add options for the split proportion, whether to split adaptively
	*change plot function to use dashed line if adaptive is TRUE for the small sample
size region. 
2016-05-18 Yang Feng <yang.feng@columbia.edu> Version 0.8
	*try out the implementation with adaptive choice of sample size for the order statistics
	*change the order statistics selection using the exact formula
2016-05-14 Yang Feng <yang.feng@columbia.edu> Version 0.7
	*change the parallel computing schedule to multiple splits
2016-05-13 Yang Feng <yang.feng@columbia.edu> Version 0.6
	*change the bootstrap calculation to an explicit formula. The algorithm is more efficient now.
	*change the starting point of the ROC curve to the alpha value for which it is possible to control the type I error with probability 1-delta
2016-05-08 Yang Feng <yang.feng@columbia.edu> Version 0.5
	*change the mc.cores=1 in the Vignettes to be compatible with windows. 
2016-04-18 Yang Feng <yang.feng@columbia.edu> Version 0.4
	*change the default alphalist range. 
2016-03-06 Yang Feng <yang.feng@columbia.edu> Version 0.3
	*add ensemble implementation for npc, nproc.
2016-02-21 Yang Feng <yang.feng@columbia.edu> Version 0.2
        * set random seed to 0 (customizable) for reproducibility in all functions
	* add implementation of np-roc with pre-specified confidence level with conf parameter
	* change SVM implementation to use raw scores instead of probability
        * write a core function for nproc to speed up the process
	* add functionality of running several classifiers at the same time for nproc
	* add a plot function for nproc class, which can compare several classifiers
	* added a vignette for a detailed demo of the package
	
	
