Rcpp (>= 0.12.17), ggplot2, PerformanceAnalytics, xts, zoo,
RobStatTM, stats

Computes the influence functions time series of the returns for the risk and
performance measures as mentioned in Chen and Martin (2018)
<https://www.ssrn.com/abstract=3085672>, as well as in Zhang et al. (2019)
<https://www.ssrn.com/abstract=3415903>. Also evaluates estimators influence
functions at a set of parameter values and plots them to display the shapes of
the influence functions.

Estimates of Standard Errors for Risk and Performance Measures
Anthony Christidis <anthony.christidis@stat.ubc.ca>,
Xin Chen <chenx26@uw.edu>
Estimates of standard errors of popular risk and performance
measures for asset or portfolio returns using methods as described in
Chen and Martin (2019) <https://ssrn.com/abstract=3085672>.
RPEIF, RPEGLMEN, PerformanceAnalytics, xts, zoo, robustbase,
boot, sandwich

RPEIF, RPEGLMEN, PerformanceAnalytics, xts, zoo, boot,
sandwich

xts, zoo, boot, sandwich, RPEIF, RPEGLMEN,
PerformanceAnalytics

Estimates of standard errors of popular risk and performance
measures for asset or portfolio returns using methods as described in
Chen and Martin (2018) <https://www.ssrn.com/abstract=3085672>.
xts, zoo, boot, sandwich, RPEIF, RPEGLMEN,

xts, zoo, boot, RPEIF, RPEGLMEN, RobStatTM

Estimates of standard errors of popular risk and performance
measures for asset or portfolio returns using methods as described in
Chen and Martin (2021) <doi:10.21314/JOR.2020.446>.

Reduced Piecewise Exponential Estimate/Test Software
c(person("Gang", "Han", role = c("aut", "cre"),
email = "hangang.true@gmail.com"),
person("Yu", "Zhang", role = "aut", email = "zyww9088@gmail.com"))
This reduced piecewise exponential survival software implements the likelihood ratio test and backward elimination procedure in Han, Schell, and Kim (2012 <doi:10.1080/19466315.2012.698945>, 2014 <doi:10.1002/sim.5915>), and Han et al. (2016 <doi:10.1111/biom.12590>). Inputs to the program can be either times when events/censoring occur or the vectors of total time on test and the number of events. Outputs of the programs are times and the corresponding p-values in the backward elimination. Details about the model and implementation are given in Han et al. 2014. This program can run in R version 3.2.2 and above.