RLadyBug-package: Analysis of infectious diseases using stochastic epidemic...
In RLadyBug: Analysis of Infectious Diseases using Stochastic Epidemic Models

Description Details Author(s) References See Also Examples

RLadyBug is an S4-package for the simulation, visualization and estimation of stochastic epidemic models in R. Utilizing the Susceptible-Exposed-Infected-Recovered (SEIR) model as mathematical framework, maximum likelihood and Bayesian inference can be performed to estimate the parameters in data from a single outbreak of an infectious disease typical in e.g. disease transmission experiments. The (twin)SIR modelling of infectious disease surveillance data introduced with version 0.5 has (with version 0.7) been migrated to the package surveillance (>= 1.3.0).

Package:	RLadyBug
Type:	Package
Version:	0.7-1
Date:	2012-02-19
License:	see file LICENSE

Likelihood and Bayesian inference for the SEIR-modelling of a single outbreak in a heterogenous population as in Höhle et al. (2005) using an additive intensity model. Typical examples are animal disease transmission experiments. Event observations can be missing.
Analysis of the same type of data structure based on approximate inference using Poisson regression as in Klinkenberg et al. (2002)

The aim of the package is to take a step towards statistical software supporting parameter estimation, the calculation of confidence intervals and hypothesis testing for stochastic epidemic models.

The package works by using rJava to interface Java code doing the actual MCMC inference. Since the system.out and system.err from the java call are saved in the current working directory it is necessary for the seir function to work that write permissions to the the current path (getwd()) exist.

Michael Höhle and Ulrike Feldmann with contributions by Sebastian Meyer

Maintainer: Michael Höhle hoehle@math.su.se

RLadyBug – An R package for working with stochastic epidemic models (2007), M. Höhle and U. Feldmann, Computational Statistics and Data Analysis, 52(2), pp. 680–686.

Höhle, M., Jørgensen, E. and O'Neill, P.D. (2005), Journal of the Royal Statistical Society, Series C, 54(2), pp. 349–366.

Klinkenberg, D., De Bree, J., Laevens, H. and De Jong, M. C. M. (2002), Within- and between-pen transmission of Classical Swine Fever Virus: a new method to estimate the basic reproduction ratio from transmission experiments, Epidemiol. Infect., 128, 293-299.

Package surveillance