Nothing
Code
cff_read(c("abcde", "b"))
Condition
Error in `cff_read()`:
! Use a single value, `path` has length 2
Code
cff_read("abcde")
Condition
Error in `file_exist_abort()`:
! 'abcde' doesn't exist. Check the '.' directory
Code
cff_read_cff_citation("a")
Condition
Error in `file_exist_abort()`:
! 'a' doesn't exist. Check the '.' directory
Code
cff_read_description("a")
Condition
Error in `file_exist_abort()`:
! 'a' doesn't exist. Check the '.' directory
Code
cff_read_bib("a")
Condition
Error in `file_exist_abort()`:
! 'a' doesn't exist. Check the '.' directory
Code
d
Output
type: article
title: 'cffr: Generate Citation File Format Metadata for R Packages'
authors:
- family-names: Hernangómez
given-names: Diego
year: '2021'
journal: Journal of Open Source Software
publisher:
name: The Open Journal
volume: '6'
issue: '67'
doi: 10.21105/joss.03900
url: https://doi.org/10.21105/joss.03900
copyright: All rights reserved
notes: 'Publisher: The Open Journal'
start: '3900'
Code
cff_read_citation("a")
Condition
Error in `file_exist_abort()`:
! 'a' doesn't exist. Check the '.' directory
Code
s <- cff_read(f, meta = "aa")
Message
! `meta` should be "NULL" or a <packageDescription> object not a string. Using `meta = NULL`
Code
cffobj
Output
cff-version: 1.2.0
message: 'To cite package "surveillance" in publications use:'
type: software
license: GPL-2.0-only
title: 'surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic
Phenomena'
version: 1.19.1
doi: 10.32614/CRAN.package.surveillance
abstract: Statistical methods for the modeling and monitoring of time series of counts,
proportions and categorical data, as well as for the modeling of continuous-time
point processes of epidemic phenomena. The monitoring methods focus on aberration
detection in count data time series from public health surveillance of communicable
diseases, but applications could just as well originate from environmetrics, reliability
engineering, econometrics, or social sciences. The package implements many typical
outbreak detection procedures such as the (improved) Farrington algorithm, or the
negative binomial GLR-CUSUM method of Höhle and Paul (2008) <https://doi.org/10.1016/j.csda.2008.02.015>.
A novel CUSUM approach combining logistic and multinomial logistic modeling is also
included. The package contains several real-world data sets, the ability to simulate
outbreak data, and to visualize the results of the monitoring in a temporal, spatial
or spatio-temporal fashion. A recent overview of the available monitoring procedures
is given by Salmon et al. (2016) <https://doi.org/10.18637/jss.v070.i10>. For the
retrospective analysis of epidemic spread, the package provides three endemic-epidemic
modeling frameworks with tools for visualization, likelihood inference, and simulation.
hhh4() estimates models for (multivariate) count time series following Paul and
Held (2011) <https://doi.org/10.1002/sim.4177> and Meyer and Held (2014) <https://doi.org/10.1214/14-AOAS743>.
twinSIR() models the susceptible-infectious-recovered (SIR) event history of a fixed
population, e.g, epidemics across farms or networks, as a multivariate point process
as proposed by Höhle (2009) <https://doi.org/10.1002/bimj.200900050>. twinstim()
estimates self-exciting point process models for a spatio-temporal point pattern
of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed
by Meyer et al. (2012) <https://doi.org/10.1111/j.1541-0420.2011.01684.x>. A recent
overview of the implemented space-time modeling frameworks for epidemic phenomena
is given by Meyer et al. (2017) <https://doi.org/10.18637/jss.v077.i11>.
authors:
- family-names: Höhle
given-names: Michael
email: hoehle@math.su.se
orcid: https://orcid.org/0000-0002-0423-6702
- family-names: Meyer
given-names: Sebastian
email: seb.meyer@fau.de
orcid: https://orcid.org/0000-0002-1791-9449
- family-names: Paul
given-names: Michaela
repository: https://CRAN.R-project.org/package=surveillance
url: https://surveillance.R-Forge.R-project.org/
date-released: '2021-03-30'
contact:
- family-names: Meyer
given-names: Sebastian
email: seb.meyer@fau.de
orcid: https://orcid.org/0000-0002-1791-9449
references:
- type: article
title: 'Monitoring Count Time Series in R: Aberration Detection in Public Health
Surveillance'
authors:
- family-names: Salmon
given-names: Maëlle
- family-names: Schumacher
given-names: Dirk
- family-names: Höhle
given-names: Michael
journal: Journal of Statistical Software
year: '2016'
volume: '70'
issue: '10'
doi: 10.18637/jss.v070.i10
start: '1'
end: '35'
- type: article
title: Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance
authors:
- family-names: Meyer
given-names: Sebastian
- family-names: Held
given-names: Leonhard
- family-names: Höhle
given-names: Michael
journal: Journal of Statistical Software
year: '2017'
volume: '77'
issue: '11'
doi: 10.18637/jss.v077.i11
start: '1'
end: '55'
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