A Modified Random Survival Forest Algorithm (icRSF)
Implements a modification to the Random Survival Forests algorithm for obtaining variable importance in high dimensional datasets. The proposed algorithm is appropriate for settings in which a silent event is observed through sequentially administered, error-prone self-reports or laboratory based diagnostic tests. The modified algorithm incorporates a formal likelihood framework that accommodates sequentially administered, error-prone self-reports or laboratory based diagnostic tests. The original Random Survival Forests algorithm is modified by the introduction of a new splitting criterion based on a likelihood ratio test statistic.
Compute Sample Size that Meets Requirements for Average Power and FDR (FDRsampsize)
Defines a collection of functions to compute average power and sample size for studies that use the false discovery rate as the final measure of statistical significance.
Miscellaneous Extensions to ‘ggplot2’ (ggpmisc)
Implements extensions to ‘ggplot2’ respecting the grammar of graphics paradigm. Provides new stats to locate and tag peaks and valleys in 2D plots, a stat to add a label by group with the equation of a polynomial fitted with lm(), or R^2 or adjusted R^2 values for any model fitted with function lm(). Provides a function for flexibly converting time series to data frames suitable for plotting with ggplot(). In addition provides two stats useful for diagnosing what data are passed to compute_group() and compute_panel() functions.