dTrajObs: Log-likelihood of a trajectory for a deterministic model

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

Log-likelihood of a trajectory for a deterministic model

Description

Compute the trajectory (log-)likelihood of theta for a deterministic model defined in a fitmodel object by summing the point log-likelihoods.

Usage

dTrajObs(fitmodel, theta, initState, data, log = TRUE)

Arguments

fitmodel	a fitmodel object
theta	named numeric vector. Values of the parameters. Names should match fitmodel$thetaNames.
initState	named numeric vector. Initial values of the state variables. Names should match fitmodel$stateNames.
data	data frame. Observation times and observed data. The time column must be named "time" and the observation column must be named "obs".
log	logical (default: FALSE); whether the logarithm of the likelihood should be returned

Value

numeric value of the log-likelihood

See Also

rTrajObs

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