| calc.ro | Caclulate net reproduction number from a demographic projection matrix. |
| cetaceans | Ages of stranded dolphins |
| coale | Coale method. |
| cohort | Cohort method |
| dens.prior | Density of priors. |
| eigen.analysis | Analysis of Eigen values |
| entropy.wts | Entropy of the rescaled weights relative to uniformity. |
| Est.life.tab | Estimated life table. |
| expt.upts | Expected number of unique inputs after the final IMIS re-sample. |
| final.resamp | Final re-sampling step in Bayesian Melding using IMIS. |
| gen.time | Generation time |
| HP.CI | Helligman-Pollard confidence intervals with 9 parameters |
| HP.mod | Heligman-Pollard parameter estimator using Bayesian Melding with Incremental Mixture Importance Sampling. |
| hp.nqx | Heligman-Pollard parameter conversion to age-specifc probabilites of death. |
| HP.pred | Prediction of Heligman-Pollard model. |
| HP.pri.start | Estimation of starting values for priors of the Heligman-Pollard model. |
| HP.priors | Heligman-Pollard Parameter prior formation. |
| keyfitz | Keyfitz and Flieger method. |
| Leslie.matrix | Leslie matrix |
| Leslie.pred | Project Leslie matrix |
| life.Leslie | Life table for Leslie matrix projections. |
| life.tab | Life table |
| like.resamp | Local Optimums and Covariance from the optimizer step. |
| ll.binom | Binomial likelihood. |
| loop.optim | Optimizer step for estimating the Heligman-Pollard Parameters using the Bayesian Melding with IMIS-opt procedure. |
| mod | Heligman-Pollard parameter coversion to age-specific probabilites of death. |
| mod.nat | Heligman-Pollard parameter coversion to natural age-specific probabilites of death. |
| mod.risk | Heligman-Pollard parameter coversion to age-specific probabilites of death due to an external risk. |
| prior.likewts | Prior likelihoods and weights. |
| samp.postopt | Multivariate Gaussian Sampling for Heligman-Pollard model estimated via Bayesian Melding. |
| Si.mod | Siler model. |
| Si.pred | Predict Siler model |
| var.rwts | Variance of the rescaled weights when estimating the Heligman-Pollard parameters using Bayesian Melding with IMIS. |