This function acts as a simple wrapper for lsoda, allowing for multiple parameter sets and
initial conditions. It also allows `lsoda`

to be used within the idmodelr framework.

solve_ode( model = NULL, inits = NULL, params = NULL, times = NULL, as.data.frame = TRUE, ... )

model | A model formatted as required by |
---|---|

inits | The initial state (states) of the model. Can either be supplied as a named vector or as a matrix with each row representing a parameter. |

params | A named vector or matrix of parameters. The matrix must have a row for each parameter and if |

times | A numeric vector of the times for which explicit model estimates are required, this does not effect the timestep used by the solver |

as.data.frame | A logical (defaults to |

... | Additional arguments to pass to |

A dataframe or lsoda object containing a single or multiple model trajectories

## Intialise N = 100000 I_0 = 1 S_0 = N - I_0 R_0 = 1.1 beta = R_0 ##Time for model to run over tbegin = 0 tend = 50 times <- seq(tbegin, tend, 1) ##Vectorise input parameters <- as.matrix(c(beta = beta)) inits <- as.matrix(c(S = S_0, I = I_0)) solve_ode(model = SI_ode, inits, parameters, times, as.data.frame = TRUE)#> # A tibble: 51 x 3 #> time S I #> <dbl> <dbl> <dbl> #> 1 0 99999 1 #> 2 1 99997. 3.00 #> 3 2 99991. 9.02 #> 4 3 99972. 27.1 #> 5 4 99919. 81.4 #> 6 5 99756. 244. #> 7 6 99270. 730. #> 8 7 97839. 2161. #> 9 8 93778. 6222. #> 10 9 83382. 16618. #> # … with 41 more rows