deBInfer: Bayesian Inference for Differential Equations

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A Bayesian framework for parameter inference in differential equations. This approach offers a rigorous methodology for parameter inference as well as modeling the link between unobservable model states and parameters, and observable quantities. Provides templates for the DE model, the observation model and data likelihood, and the model parameters and their prior distributions. A Markov chain Monte Carlo (MCMC) procedure processes these inputs to estimate the posterior distributions of the parameters and any derived quantities, including the model trajectories. Further functionality is provided to facilitate MCMC diagnostics and the visualisation of the posterior distributions of model parameters and trajectories.

Author
Philipp H Boersch-Supan [aut, cre], Leah R Johnson [aut], Sadie J Ryan [aut]
Date of publication
2016-09-14 21:44:04
Maintainer
Philipp H Boersch-Supan <pboesu@gmail.com>
License
GPL-3
Version
0.4.1

View on CRAN

Man pages

chytrid
Chytrid fungus data set
debinfer_par
debinfer_par
deinits
Get starting/fixed values of DE initial values
de_mcmc
de_mcmc
depars
Get starting/fixed values of DE parameters
is.debinfer_result
is.debinfer_result
logd_prior
logd_prior
logistic
Logistic growth data set
log_post_params
log_post_params
log_prior_params
log_prior_params
pairs.debinfer_result
Pairwise posterior marginals
plot.debinfer_result
Plot inference outputs
plot.post_sim_list
Plot posterior trajectory
post_prior_densplot
Plot posterior marginals and corresponding priors
post_sim
post_sim
prior_draw_rev
prior_draw_rev
propose_joint_rev
propose_joint
propose_single_rev
propose_single_rev
reshape_post_sim
Reshape posterior model solutions
setup_debinfer
setup_debinfer
solve_de
solve_de
summary.debinfer_result
Summary of the inference results
update_sample_rev
update_sample_rev

Files in this package

deBInfer
deBInfer/inst
deBInfer/inst/CITATION
deBInfer/inst/doc
deBInfer/inst/doc/deBInfer_compiled_code.pdf
deBInfer/inst/doc/logistic_ode_example.pdf
deBInfer/inst/doc/chytrid_dede_example.pdf
deBInfer/inst/doc/chytrid_dede_example.R
deBInfer/inst/doc/deBInfer_compiled_code.pdf.asis
deBInfer/inst/doc/logistic_ode_example.R
deBInfer/inst/doc/chytrid_dede_example.Rmd
deBInfer/inst/doc/logistic_ode_example.Rmd
deBInfer/tests
deBInfer/tests/testthat.R
deBInfer/tests/testthat
deBInfer/tests/testthat/test_likelihood_eval.R
deBInfer/tests/testthat/test_inference_logistic.R
deBInfer/tests/testthat/test_debinfer_par.R
deBInfer/NAMESPACE
deBInfer/data
deBInfer/data/logistic.rda
deBInfer/data/chytrid.rda
deBInfer/R
deBInfer/R/setup_mcmc.R
deBInfer/R/de_solver.R
deBInfer/R/de_mcmc_rev.R
deBInfer/R/data_doc.R
deBInfer/R/mcmc_plotting.R
deBInfer/R/debinfer_utils.R
deBInfer/vignettes
deBInfer/vignettes/methods-in-ecology-and-evolution.csl
deBInfer/vignettes/debinfer.bib
deBInfer/vignettes/deBInfer_compiled_code.pdf.asis
deBInfer/vignettes/epsilon-sensitivity.pdf
deBInfer/vignettes/chytrid_dede_example.Rmd
deBInfer/vignettes/logistic_ode_example.Rmd
deBInfer/README.md
deBInfer/MD5
deBInfer/build
deBInfer/build/vignette.rds
deBInfer/DESCRIPTION
deBInfer/man
deBInfer/man/log_post_params.Rd
deBInfer/man/debinfer_par.Rd
deBInfer/man/pairs.debinfer_result.Rd
deBInfer/man/summary.debinfer_result.Rd
deBInfer/man/plot.debinfer_result.Rd
deBInfer/man/depars.Rd
deBInfer/man/logd_prior.Rd
deBInfer/man/logistic.Rd
deBInfer/man/post_prior_densplot.Rd
deBInfer/man/solve_de.Rd
deBInfer/man/prior_draw_rev.Rd
deBInfer/man/plot.post_sim_list.Rd
deBInfer/man/is.debinfer_result.Rd
deBInfer/man/update_sample_rev.Rd
deBInfer/man/de_mcmc.Rd
deBInfer/man/log_prior_params.Rd
deBInfer/man/propose_joint_rev.Rd
deBInfer/man/propose_single_rev.Rd
deBInfer/man/post_sim.Rd
deBInfer/man/setup_debinfer.Rd
deBInfer/man/reshape_post_sim.Rd
deBInfer/man/chytrid.Rd
deBInfer/man/deinits.Rd