js.lnl: Likelihood function for Jolly-Seber model using...

Description Usage Arguments Details Value Author(s) References

View source: R/js.lnl.r


For a given set of parameters and data, it computes -2*log Likelihood value but does not include data factorials. Factorials for unmarked are not needed but are included in final result by js so the result matches output from MARK for the POPAN model.


js.lnl(par, model_data, debug = FALSE, nobstot, jsenv)



vector of parameter values


a list that contains: 1)imat-list of vectors and matrices constructed by process.ch from the capture history data, 2)Phi.dm design matrix for Phi constructed by create.dm, 3)p.dm design matrix for p constructed by create.dm, 4)pent.dm design matrix for probability of entry constructed by create.dm, 5) N.dm design matrix for estimates of number of animals not caught from super-population constructed by create.dm, 6)Phi.fixed matrix with 3 columns: ch number(i), occasion number(j), fixed value(f) to fix phi(i,j)=f, 7) p.fixed matrix with 3 columns: ch number(i), occasion number(j), 8) pent.fixed matrix with 3 columns: ch number(i), occasion number(j), fixed value(f) to fix pent(i,j)=f, and 9) time.intervals intervals of time between occasions if not all 1 fixed value(f) to fix p(i,j)=f


if TRUE will printout values of par and function value


number of unique caught at least once by group if applicable


environment for js to update iteration counter


This functions uses cjs.lnl and then supplements with the remaining calculations to compute the likelihood for the POPAN formulation (Arnason and Schwarz 1996) of the Jolly-Seber model.


-log likelihood value, excluding data (ui) factorials which are added in js after optimization to match MARK


Jeff Laake


Schwarz, C. J., and A. N. Arnason. 1996. A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics 52:860-873.

marked documentation built on Dec. 9, 2019, 9:06 a.m.