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/.

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