fitmodel: Constructor of fitmodel object

In sbfnk/fitR: Tool box for fitting dynamic infectious disease models to time series

Constructor of fitmodel object

Description

A fitmodel object is a list that stores some variables and functions that will be useful to simulate and fit your model during the course.

Usage

fitmodel(
  name = NULL,
  stateNames = NULL,
  thetaNames = NULL,
  simulate = NULL,
  rPointObs = NULL,
  dPrior = NULL,
  dPointObs = NULL
)

Arguments

name	character. Name of the model (required).
stateNames	character vector. Names of the state variables i.e. c("S","I","R") (required).
thetaNames	character vector. Names of the parameters i.e. c("R_0","infectiousPeriod") (required).
simulate	R-function to simulate forward the model (required). This function takes 3 arguments: theta named numeric vector. Values of the parameters. Names should match thetaNames. initState named numeric vector. Initial values of the state variables. Names should match stateNames. times numeric vector. Time sequence for which the state of the model is wanted; the first value of times must be the initial time, i.e. the time of initState. and returns a data.fame containing the simulated trajectories that is the values of the state variables (1 per column) at each observation time (1 per row). The first column is time.
rPointObs	R-function that generates a (randomly sampled) observation point from a model point, using an observation model (optional). It thus acts as an inverse of dPointObs (see below). This function takes 2 arguments modelPoint named numeric vector. State of the model at a given point in time. theta named numeric vector. Values of the parameters. Names should match thetaNames. and returns an observation point
dPrior	R-function that evaluates the prior density of the parameters at a given theta (optional). The function should take 2 arguments: theta named numeric vector. Values of the parameters. Names should match thetaNames. log boolean. determines whether the logarithm of the prior density should be returned. and returns the (logged, if requested) value of the prior density distribution.
dPointObs	R-function that evaluates the likelihood of one data point given the state of the model at the same time point. This function takes 4 arguments: dataPoint named numeric vector. Observation time and observed data point. modelPoint named numeric vector containing the state of the model at the observation time point. theta named numeric vector. Parameter values. Useful since parameters are usually needed to compute the likelihood (i.e. reporting rate). log boolean. determines whether the logarithm of the likelihood should be returned. and returns the (log-)likelihood. (optional)

Value

a fitmodel object that is a list of 7 elements:

• name character, name of the model

• stateNames vector, names of the state variables.

• thetaNames vector, names of the parameters.

• simulate R-function to simulate forward the model; usage: simulate(theta,initState,times).

• rPointObs R-function to generate simulated observations; usage: rPointObs(modelPoint, theta).

• dPrior R-function to evaluate the log-prior of the parameter values; usage: dPrior(theta).

• dPointObs R-function to evaluate the log-likelihood of one data point; usage: dPointObs(dataPoint, modelPoint, theta, log).

See Also

testFitmodel

sbfnk/fitR documentation built on July 18, 2023, 3:28 p.m.