c(person("Song", "Zhai", role = c("aut", "cre"), email =
"zsviolet1993@gmail.com"))
Construct pharmacogenomics (PGx) polygenic risk score (PRS) with PRS-PGx-Unadj (unadjusted), PRS-PGx-CT (clumping and thresholding), PRS-PGx-L, -GL, -SGL (penalized regression), PRS-PGx-Bayes (Bayesian regression). Package is based on ''Pharmacogenomics Polyenic Risk Score for Drug Response Prediction Using PRS-PGx Methods'' by Zhai, S., Zhang, H., Mehrotra, D.V., and Shen, J., 2021 (submitted).

Stochastic Simulation of Streamflow Time Series using Phase
Randomization
c(person("Manuela", "Brunner", role = c("aut", "cre"),
email = "manuela.brunner@wsl.ch",
comment = c(ORCID = "0000-0001-8824-877X")),
person("Reinhard", "Furrer", role = c("aut"),
email = "reinhard.furrer@math.uzh.ch",
comment = c(ORCID = "0000-0002-6319-2332")))
Manuela Brunner [aut, cre] (<https://orcid.org/0000-0001-8824-877X>),
Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>)
Provides a simulation framework to simulate streamflow time series with similar
main characteristics as observed data. These characteristics include the distribution of daily
streamflow values and their temporal correlation as expressed by short- and long-range
dependence. The approach is based on the randomization of the phases of the Fourier
transform. We further use the flexible four-parameter Kappa distribution, which allows
for the extrapolation to yet unobserved low and high flows.

Provides a simulation framework to simulate streamflow time series with similar
main characteristics as observed data. These characteristics include the distribution of daily
streamflow values and their temporal correlation as expressed by short- and long-range
dependence. The approach is based on the randomization of the phases of the Fourier
transform. We further use the flexible four-parameter Kappa distribution, which allows
for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. A detailed description of
the simulation approach and an application example can be found
in <https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-142/>.