Real-Time Disease Surveillance
Extracts fixed effect coefficients from a rtsFit object
Fixed effect confidence intervals for a rtsFit object
Extracts the estimates of the covariance parameters
Create sf object from point location data
Extracts the family from a grid object.
Extracts the family from a rtsFit object.
Fitted values from a rtsFit object
Extracts the fixed effect estimates
Extracts the formula from a grid object.
Extracts the formula from a rtsFit object.
An rts grid object
Extracts the log-likelihood from an rtsFit object
Extract predictions from a grid object
Predict from a rtsFit object
Prints an rtsFit fit output
Prints an rtsFitSummary fit output
Generates a progress bar
Extracts the random effect estimates
Residuals method for a grid object
Residuals method for a rtsFit object
tools:::Rd_package_title("rts2")
Summarizes a grid object
Summary method for class "rtsFit"
Calculate Variance-Covariance matrix for a maximum likelihood object s...
Extract the Variance-Covariance matrix for a rtsFit object
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/>.