Description Usage Arguments Details Value Author(s) Examples

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

1 2 3 4 5 6 7 | ```
## 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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
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);
``` |

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