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rts2  

Real-Time Disease Surveillance
View on CRAN: Click here


Download and install rts2 package within the R console
Install from CRAN:
install.packages("rts2")

Install from Github:
library("remotes")
install_github("cran/rts2")

Install by package version:
library("remotes")
install_version("rts2", "0.7.7")



Attach the package and use:
library("rts2")
Maintained by
Sam Watson
[Scholar Profile | Author Map]
First Published: 2022-03-21
Latest Update: 2023-04-18
Description:
Supports modelling real-time case data to facilitate the real-time surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts, and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by Diggle et al. (2013) and we provide both the low-rank approximation for Gaussian processes described by Solin and S
How to cite:
Sam Watson (2022). rts2: Real-Time Disease Surveillance. R package version 0.7.7, https://cran.r-project.org/web/packages/rts2. Accessed 26 Mar. 2025.
Previous versions and publish date:
0.3 (2022-03-21 09:30), 0.4 (2022-10-27 17:02), 0.5 (2023-04-18 13:40), 0.6.1 (2024-01-25 13:20), 0.7.1 (2024-03-01 19:50), 0.7.2 (2024-03-08 10:30), 0.7.4 (2024-04-04 01:40), 0.7.5 (2024-06-24 20:10), 0.7.6 (2024-09-06 14:30)
Other packages that cited rts2 R package
View rts2 citation profile
Other R packages that rts2 depends, imports, suggests or enhances
Complete documentation for rts2
Functions, R codes and Examples using the rts2 R package
Some associated functions: birmingham_crime . boundary . create_points . example_points . grid . print.mcmlrts . progress_bar . rts2-package . summary.mcmlrts . 
Some associated R codes: RcppExports.R . data_functions.R . griddata_class.R . print_mcmlrts.R . rts2-package.R . stanmodels.R .  Full rts2 package functions and examples
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