How to Install and Uninstall r-cran-surveillance Package on Kali Linux

Last updated: May 14,2024

1. Install "r-cran-surveillance" package

Please follow the guidelines below to install r-cran-surveillance on Kali Linux

$ sudo apt update $ sudo apt install r-cran-surveillance

2. Uninstall "r-cran-surveillance" package

This guide let you learn how to uninstall r-cran-surveillance on Kali Linux:

$ sudo apt remove r-cran-surveillance $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-surveillance package on Kali Linux

Package: r-cran-surveillance
Version: 1.22.1-1
Installed-Size: 6610
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-cran-sp (>= 1.0-15), r-cran-xtable (>= 1.7-0), r-cran-rcpp (>= 0.11.1), r-cran-polycub (>= 0.8.0), r-cran-mass, r-cran-matrix, r-cran-nlme, r-cran-spatstat.geom, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 13.1)
Recommends: r-cran-gridextra (>= 2.0.0), r-cran-lattice (>= 0.20-44), r-cran-colorspace, r-cran-scales, r-cran-animation, r-cran-msm, r-cran-spc, r-cran-coda, r-cran-spdep, r-cran-numderiv, r-cran-maxlik, r-cran-gsl, r-cran-quadprog, r-cran-memoise, r-cran-polyclip, r-cran-intervals, r-cran-sf, r-cran-tinytest (>= 1.2.4), r-cran-knitr
Size: 5592316
SHA256: 12e99460b82a34ad7de8f05dd097c1e952a73b122bf62aec26522e3b5e77202d
SHA1: f229cce9d67e101c86ca5f43dfca0ff6a8d27e46
MD5sum: 6f8c96480dd53eef494f59b460fc3dfe
Description: GNU R package for the Modeling and Monitoring of Epidemic Phenomena
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) . 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) .
.
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)
and Meyer and Held (2014)
. 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) .
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)
. A recent overview of the
implemented space-time modeling frameworks for epidemic phenomena is
given by Meyer et al. (2017) .
Description-md5:
Homepage: https://cran.r-project.org/package=surveillance
Tag: field::medicine, implemented-in::r, interface::commandline,
role::program
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-surveillance/r-cran-surveillance_1.22.1-1_amd64.deb