rts2

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) doi:10.1214/13-STS441 and we provide both the low-rank approximation for Gaussian processes described by Solin and Särkkä (2020) doi:10.1007/s11222-019-09886-w and Riutort-Mayol et al (2023) doi:10.1007/s11222-022-10167-2 and the nearest neighbour Gaussian process described by Datta et al (2016) doi:10.1080/01621459.2015.1044091. 'cmdstanr' can be downloaded at https://mc-stan.org/cmdstanr/.

Last 30 days

This package has been downloaded 294 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,693 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Oct 24, 2024 with 95 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.