c(person(given = "Robin",
family = "Lovelace",
role = c("aut", "cre"),
email = "rob00x@gmail.com",
comment = c(ORCID = "0000-0001-5679-6536")),
person(given = "Martin",
family = "Lucas-Smith",
role = "aut"),
person(given = "Eric",
family = "Krueger",
role = "ctb"),
person(given = "Joey",
family = "Talbot",
role = "aut",
email = "j.d.talbot@leeds.ac.uk",
comment = c(ORCID = "0000-0002-6520-4560")))
An interface to the cycle routing/data services provided by
'CycleStreets', a not-for-profit social enterprise and advocacy
organisation.  The application programming interfaces (APIs) provided
by 'CycleStreets' are documented at
(<https://www.cyclestreets.net/api/>).  The focus of this package is
the journey planning API, which aims to emulate the routes taken by a
knowledgeable cyclist.  An innovative feature of the routing service
of its provision of fastest, quietest and balanced profiles.  These
represent routes taken to minimise time, avoid traffic and compromise
between the two, respectively.
geodist, httr, jsonlite, magrittr, sf, stringr

Cyclomatic complexity is a software metric (measurement), used to
indicate the complexity of a program. It is a quantitative measure of the number
of linearly independent paths through a program's source code. It was developed
by Thomas J. McCabe, Sr. in 1976.

Cyclomatic complexity is a software metric (measurement),
used to indicate the complexity of a program. It is a quantitative
measure of the number of linearly independent paths through a program's
source code. It was developed by Thomas J. McCabe, Sr. in 1976.

Tools for calculating coordinate representations of
hypocycloids, epicyloids, hypotrochoids, and epitrochoids
(altogether called 'cycloids' here) with different scaling
and positioning options. The cycloids can be visualised with
any appropriate graphics function in R.

Survival Modeling with a Periodic Hazard Function
c(person("Eliezer", "Gurarie", role = c("aut", "cre"), email = "egurarie@umd.edu"), person("Thompson", "Peter", role = "aut"))
Modeling periodic mortality (or other time-to event) processes from right-censored data. Given observations of a process with a known period (e.g. 365 days, 24 hours), functions determine the number, intensity, timing, and duration of peaks of periods of elevated hazard within a period.  The underlying model is a mixed wrapped Cauchy function fitted using maximum likelihoods (details in Gurarie et al. (2020) <doi:10.1111/2041-210X.13305>). The development of these tools was motivated by the strongly seasonal mortality patterns observed in many wild animal populations, such that the respective periods of higher mortality can be identified as "mortality seasons".
flexsurv, lubridate, magrittr, mvtnorm, plyr, scales, stats,
survival
Eliezer Gurarie [aut, cre],
Thompson Peter [aut]