2018-11-10 Yang Feng Version 2.1.4 *improved the efficiency for computing Neyman-Pearson classifiers. 2018-02-13 Yang Feng Version 2.1.1 *added the slda classifier and the nonparametric naive bayes classifier *added the adaptive split ratio option 2017-09-23 Yang Feng Version 2.1 *change the option of shiny for split numbers 2017-09-16 Yang Feng Version 2.0.9 *speed up the calculation for order statistics *minor changes on plot legends and line width 2017-08-17 Yang Feng Version 2.0.8 *remove the custom option *remove the nproc line, only keeps the band version 2017-02-13 Yang Feng Version 2.0.6 *add implementation for roc with cross-validation 2017-01-18 Yang Feng Version 2.0.5 *pass additional arguments to different classifiers via … 2017-01-11 Yang Feng Version 2.0.4 *improve the memory use for the outer function in find.order function 2016-09-18 Yang Feng Version 2.0.1 *using only the cutoffs from class 0 to create the NP-ROC band to match the theory. 2016-09-14 Yang Feng Version 2.0 *change the implementation of the interpolation for ROC confidence band by using a piecewise constant function to approximate the upper and lower bounds. *using all the possible cutoff from class 1 and class 0 to create the NP-ROC band. 2016-09-08 Yang Feng Version 1.9 *change the implementation of the npc. In particular, originally, we are looking for the order statistic that satisfies the type I error upper bound with high-probability. Now, we investigate all possible cutoffs and evaluate its corresponding upper and lower bounds of type I and type II errors. This way, we do not need to impose the minimal sample size requirement. *change the implementation of the ROC confidence band, here, the lower bound represents the upper bounds of type I error and 1-upper bounds of type II error. The upper bound represents the lower bounds of type I error and 1-lower bounds of type II error. Upon this revision, the comparison between two methods is more reasonable and has theoretical support. 2016-08-22 Yang Feng Version 1.4 *add the comparison between two NP-ROC curves 2016-08-15 Yang Feng Version 1.3 *fix the errors when the input x is a vector 2016-08-08 Yang Feng Version 1.2 *change the package title *add the reference to the nproc paper in arxiv 2016-05-22 Yang Feng 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 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 Version 0.7 *change the parallel computing schedule to multiple splits 2016-05-13 Yang Feng 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 Version 0.5 *change the mc.cores=1 in the Vignettes to be compatible with windows. 2016-04-18 Yang Feng Version 0.4 *change the default alphalist range. 2016-03-06 Yang Feng Version 0.3 *add ensemble implementation for npc, nproc. 2016-02-21 Yang Feng 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