f_log: Log likelihood of the stochastic SIR model

In rmorsomme/PDSIR: Data-augmentation Marko chain Monte Carlo for Fitting the Stochastic SIR Model to Incidence Counts

Log likelihood of the stochastic SIR model

Description

allows non-Markovian dynamics through Weibull-distribution infectious periods (Streftaris and Gibson, 2004) allows generalized SIR process (Severo, 1969) Severo, N. C. (1969). Generalizations of some stochastic epidemic models. Mathematical Biosciences, 4(3-4), 395-402. Streftaris, G., & Gibson, G. J. (2004). Bayesian inference for stochastic epidemics in closed populations. Statistical Modelling, 4(1), 63-75.

Usage

f_log(theta, SS, gener, b, iota_dist = "exponential")

Arguments

theta	current values of the parameters for the SIR
SS	sufficient statistics of the current configuration of the latent data
gener	generalized
b	parameter of generalized
iota_dist	distribution of infection periods

Value

log likelihood

rmorsomme/PDSIR documentation built on April 27, 2023, 2:56 p.m.