A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler'
Permissions Checker
c(person("Peter", "Meissner", role = c("aut", "cre"),
email = "retep.meissner@gmail.com"),
person("Oliver", "Keys", role = "ctb"))
Provides a 'Robotstxt' ('R6') class and accompanying methods to
parse and check 'robots.txt' files. Data fields are provided as
data frames and vectors. Permissions can be checked by providing
path character vectors and optional bot names.
Peter Meissner [aut, cre],
Oliver Keys [ctb]

c(
person(
"Peter", "Meissner", role = c("aut", "cre"),
email = "retep.meissner@gmail.com"
),
person("Oliver", "Keys", role = "ctb"),
person("Rich", "Fitz John", role = "ctb")
)
Provides functions to download and parse 'robots.txt' files.
Ultimately the package makes it easy to check if bots
(spiders, scrapers, ...) are allowed to access specific
resources on a domain.
Peter Meissner [aut, cre],
Oliver Keys [ctb],
Rich Fitz John [ctb]

Provides functions to download and parse 'robots.txt' files.
Ultimately the package makes it easy to check if bots
(spiders, crawler, scrapers, ...) are allowed to access specific
resources on a domain.

c(
person(
"Peter", "Meissner", role = c("aut", "cre"),
email = "retep.meissner@gmail.com"
),
person(
"Kun", "Ren", email = "mail@renkun.me", role = c("aut", "cph"),
comment = "Author and copyright holder of list_merge.R."
),
person("Oliver", "Keys", role = "ctb", comment = "original release code review"),
person("Rich", "Fitz John", role = "ctb", comment = "original release code review")
)
Peter Meissner [aut, cre],
Kun Ren [aut, cph] (Author and copyright holder of list_merge.R.),
Oliver Keys [ctb] (original release code review),
Rich Fitz John [ctb] (original release code review)

Three-Step Regression and Inference for Cellwise and Casewise
Contamination
Three-step regression and inference for cellwise and casewise contamination.

Robust Regression with Compositional Covariates
c(person(given = "Aditya", family = "Mishra", role = c("aut", "cre"),
email = "amishra@flatironinstitute.org"),
person(given = "Christian", family = "Muller", role = "ctb"))
We implement the algorithm estimating the parameters of the robust regression model with compositional covariates. The model simultaneously treats outliers and provides reliable parameter  estimates. Publication reference: Mishra, A., Mueller, C.,(2019) <arXiv:1909.04990>.
Rcpp (>= 0.12.0), MASS, magrittr, graphics
Aditya Mishra [aut, cre],
Christian Muller [ctb]