animation, bit64, dplyr, fftw, knitr, move, parallel,
parsedate, quadprog, rmarkdown, sf, suncalc

c(person("Biplab", "Paul", role = c("aut", "cre"), email = "paul.biplab497@gmail.com"), person(c("Philip", "Tzvi"), "Reiss", role = c("aut")))
Implements a basis function or functional data analysis framework
for several techniques of multivariate analysis in continuous-time
setting. Specifically, we introduced continuous-time analogues of
several classical techniques of multivariate analysis, such as
principal component analysis, canonical correlation analysis,
Fisher linear discriminant analysis, K-means clustering, and so
on. Details are in Philip T Reiss and Biplab Paul (2022) "Continuous-time multivariate analysis";
James O Ramsay, Bernard W Silverman (2005) <ISBN:978-0-387-22751-1> "Functional Data Analysis";
James O Ramsay, Giles Hooker and Spencer Graves (2009) <ISBN:978-0-387-98185-7> "Functional Data Analysis with R and MATLAB".
Biplab Paul [aut, cre],
Philip Tzvi Reiss [aut]

phytools, viridis, knitr, rmarkdown, nlme, progress,
graphics, grDevices,
Functions for identifying, fitting, and applying continuous-time stochastic models to phylogenetic data.
The package is based on methods introduced in
Noonan et al. (2021) <doi:10.1101/2021.05.21.445056>.
Michael J. Noonan [aut, cre],
Christen H. Fleming [aut]

Censored and Truncated Quantile Regression
Estimation of quantile regression models for survival data.

Estimation of quantile regression models for survival data. The package implements the two-step estimator described in Frumento and Bottai (2017),  <doi: 10.1016/j.csda.2016.08.015>.

Retrieve and Analyze Information on Clinical Trials from Public
Registers
mongolite (>= 2.0), jsonlite, httr, curl, clipr, xml2, rvest
Provides functions for querying, retrieving and analysing protocol- and results-related information on clinical trials from two public registers, the European Union Clinical Trials Register (EUCTR, <https://www.clinicaltrialsregister.eu/>) and ClinicalTrials.gov (CTGOV, <https://clinicaltrials.gov/>). The information is transformed and then stored in a database (mongo). Functions are provided for accessing and analysing the locally stored information on the clinical trials, as well as for identifying duplicate records. The package is motivated by the need for aggregating and trend-analysing the design, conduct and outcomes across clinical trials.
person(given = "Ralf",
family = "Herold",
role = c("aut", "cre"),
email = "ralf.herold@mailbox.org",
comment = c(ORCID = "0000-0002-8148-6748"))