BDloglikelihood.PO: Calculate log likelihood of Partially Observed BD process
In DOBAD: Analysis of Discretely Observed Linear Birth-and-Death(-and-Immigration) Markov Chains

Description Usage Arguments Details Value Author(s) Examples

Calculates the log likelihood of a "partially observed birth-death-immigration process."

## S3 method for class 'CTMC_PO_1'
BDloglikelihood.PO(partialDat, L, m, nu,  n.fft = 1024)
## S3 method for class 'CTMC_PO_many'
BDloglikelihood.PO(partialDat, L, m, nu,  n.fft = 1024)
## S3 method for class 'list'
BDloglikelihood.PO(partialDat, L, m, nu,  n.fft = 1024)
BDloglikelihood.PO(partialDat, L, m, nu, n.fft = 1024)

`L`	lambda, birth rate.
`m`	mu, death rate.
`nu`	nu, Immigration rate.
`partialDat`	Either of class "CTMC_PO_many", or of class "CTMC_PO_1" or the latter's analog in list form, ie a list with the two components "states" and "times" for the "list" and default versions of this method.
`n.fft`	precision for riemann integration / fast fourier transform.

Immigration can be arbitrary here. Calculates likelihood of the b-d-i proces when it is observed at discrete timepoints.

Real number.

charles doss

library(DOBAD)
T=25;
L <- .3
mu <- .6
beta.immig <- 1.2;
initstate <- 17;

#generate process
dat <- birth.death.simulant(t=T, lambda=L, m=mu, nu=L*beta.immig, X0=initstate);
#"observe" process
delta <- 2
partialData <- getPartialData( seq(0,T,delta), dat);
#calculate the likelihood
BDloglikelihood.PO(partialDat=partialData, L=L, m=mu, nu=beta.immig*L);