Weighted Piecewise Kernel Density Estimation
Kunyu Ye, Siyao Wang, Xudong Liu, Tianwei Yu
Weighted Piecewise Kernel Density Estimation for large data.

Contains win-ratio analysis routines for prioritized composite time-to-event
outcomes, e.g., death and non-fatal events. These routines include functions to fit
the proportional win-fractions (PW) model and to compute and plot the standardized
score process to assess the proportionality assumption.

Win Ratio Analysis of Composite Time-to-Event Outcomes
Implements various win ratio methodologies for composite endpoints of death and
non-fatal events, including the (stratified) proportional win-fractions (PW) regression models
(Mao and Wang, 2020 <doi:10.1111/biom.13382>), (stratified) two-sample tests with possibly
recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al.,
2021 <doi:10.1111/biom.13501>).

c(
person("Xi", "Liu", email = "xiliu@ucsb.edu", role = c("aut", "cre")),
person("Matthew", "Coleman", email = "matthewbcoleman@ucsb.edu", role = "aut"),
person("Alexander", "Petersen", email = "petersen@pstat.ucsb.edu", role = "aut"))
Xi Liu [aut, cre],
Matthew Coleman [aut],
Alexander Petersen [aut]
An implementation of the methodologies described in Alexander Petersen, Xi Liu and Afshin A. Divani (2019) <arXiv:1910.13418>, including global F tests, partial F tests, intrinsic
Wasserstein-infinity bands and Wasserstein density bands.

c(
person("Xi", "Liu", email = "xiliu@ucsb.edu", role = c("aut", "cre")),
person("Chao", "Zhang", email = "czhang@pstat.ucsb.edu", role = "aut"),
person("Matthew", "Coleman", email = "matthewbcoleman@ucsb.edu", role = "aut"),
person("Alexander", "Petersen", email = "petersen@pstat.ucsb.edu", role = "aut"))
Xi Liu [aut, cre],
Chao Zhang [aut],
Matthew Coleman [aut],
Alexander Petersen [aut]
Implementation of the methodologies described in 1) Alexander Petersen, Xi Liu and Afshin A. Divani (2021) <doi:10.1214/20-aos1971>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) <doi:10.1111/jtsa.12590>, including estimation, prediction, and inference of the Wasserstein autoregressive models.