Title: Compute Expected Shortfall and Value at Risk for Continuous
Description: Compute expected shortfall (ES) and Value at Risk (VaR) from a
quantile function, distribution function, random number generator or
probability density function.  ES is also known as Conditional Value at
Risk (CVaR). Virtually any continuous distribution can be specified.
The functions are vectorized over the arguments. The computations are
done directly from the definitions, see e.g. Acerbi and Tasche (2002)
Imports: stats, utils, gbutils, Rdpack (>= 0.7)

Authors@R: person(given = c("Georgi", "N."), family = "Boshnakov",

<doi:10.1111/1468-0300.00091>. Some support for GARCH models is provided,
Imports: gbutils, Rdpack (>= 0.8), fGarch

Title: Coefficient of Variation (CV) with Confidence Intervals (CI)
Authors@R: person("Maani", "Beigy", email = "manibeygi@gmail.com",
Description: Provides some easy-to-use functions and classes to calculate
variability measures such as coefficient of variation with confidence
intervals provided with all available methods. References are

Title: Efficient Design and Analysis of Cluster Randomized Trials
Authors@R: c(person(given = "Hengshi", family = "Yu", role = c("aut", "cre"),
person(given = "John A.", family = "Gallis", role ="aut",
person(given = "Fan", family = "Li", role ="aut",
person(given = "Elizabeth L.", family = "Turner", role ="aut",
Description: Constrained randomization by Raab and Butcher (2001) <doi:10.1002/1097-0258(20010215)20:3%3C351::AID-SIM797%3E3.0.CO;2-C>
is suitable for cluster randomized trials (CRTs) with a
small number of clusters (e.g., 20 or fewer). The procedure of
constrained randomization is based on the baseline values of some
cluster-level covariates specified. The intervention effect on
the individual outcome can then be analyzed through
Motivated from Li, et al. (2016) <doi:10.1002/sim.7410>, the package performs constrained randomization on the baseline
values of cluster-level covariates and cluster permutation test on the individual-level outcome for cluster randomized trials.
Packaged: 2017-11-28 18:43:07 UTC; Hengshi Yu (Oliver)