Package: isotracer 1.1.7

isotracer: Isotopic Tracer Analysis Using MCMC

Implements Bayesian models to analyze data from tracer addition experiments. The implemented method was originally described in the article "A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from Isotope Tracer Addition Experiments" by López-Sepulcre et al. (2020) <doi:10.1086/708546>.

Authors:Andrés López-Sepulcre [aut], Matthieu Bruneaux [aut, cre]

isotracer_1.1.7.tar.gz
isotracer_1.1.7.zip(r-4.5)isotracer_1.1.7.zip(r-4.4)isotracer_1.1.7.zip(r-4.3)
isotracer_1.1.7.tgz(r-4.4-x86_64)isotracer_1.1.7.tgz(r-4.4-arm64)isotracer_1.1.7.tgz(r-4.3-x86_64)isotracer_1.1.7.tgz(r-4.3-arm64)
isotracer_1.1.7.tar.gz(r-4.5-noble)isotracer_1.1.7.tar.gz(r-4.4-noble)
isotracer.pdf |isotracer.html✨
isotracer/json (API)
NEWS

# Install 'isotracer' in R:
install.packages('isotracer', repos = c('https://matthieu-bruneaux.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://gitlab.com/matthieu-bruneaux/isotracer

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • aquarium_mod - A simple aquarium network model, ready to run
  • aquarium_run - An MCMC run from a simple aquarium network model
  • eelgrass - Eelgrass phosphate incorporation data
  • lalaja - Dataset for nitrogren fluxes in a Trinidadian mountain stream
  • li2017 - Protein degradation in Arabidopsis plants
  • li2017_counts - Protein degradation in Arabidopsis plants
  • li2017_prots - Protein degradation in Arabidopsis plants
  • trini_mod - Network model for nitrogen fluxes in Trinidadian streams

On CRAN:

6.01 score 49 scripts 687 downloads 61 exports 63 dependencies

Last updated 19 days agofrom:3101d112c1. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-win-x86_64WARNINGNov 05 2024
R-4.5-linux-x86_64WARNINGNov 05 2024
R-4.4-win-x86_64WARNINGNov 05 2024
R-4.4-mac-x86_64WARNINGNov 05 2024
R-4.4-mac-aarch64WARNINGNov 05 2024
R-4.3-win-x86_64WARNINGNov 05 2024
R-4.3-mac-x86_64WARNINGNov 05 2024
R-4.3-mac-aarch64WARNINGNov 05 2024

Exports:%>%add_covariatesadd_pulse_eventas_tbl_graphas.mcmc.listavailable_priorscalculate_steady_statecompsconstant_pdelta2propdicexponential_pfilterfilter_by_groupgamma_pggflowsggtopogroupshcauchy_pmcmc_heatmapmissing_priorsnew_networkModelnormal_pparamsposterior_predictpriorsprojectprop_familyprop2deltaquick_sankeyrun_mcmcsample_fromsample_from_priorsample_paramssankeyscaled_beta_pselectset_half_lifeset_initset_obsset_paramsset_priorset_priorsset_prop_familyset_size_familyset_splitset_steadyset_toposize_familystanfit_to_named_mcmclisttidy_datatidy_dpptidy_flowstidy_mcmctidy_posterior_predicttidy_steady_statestidy_trajectoriestopotraceplotuniform_pvarnames

Dependencies:abindbackportsBHcallrcheckmateclicodacolorspacecpp11data.tabledescdistributionaldplyrfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatex2explatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Calculating derived parameters

Rendered fromtutorial-110-derived-parameters.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Case study: Trinidadian streams (Collins et al. 2016)

Rendered fromcase-study-collins-2016.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-03-14

Defining pulse or drip events

Rendered fromtutorial-040-pulse-drip-events.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2019-12-12

Handling replication

Rendered fromtutorial-020-replication.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2019-12-12

How to simulate experiments

Rendered fromtutorial-120-howto-simulations.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Including fixed effects of covariates

Rendered fromtutorial-050-fixed-effects.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-03-14

MCMC output format

Rendered fromtutorial-080-mcmc-output-format.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Post-run diagnostics and analyses

Rendered fromtutorial-090-post-run-analyses.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Posterior predictive checks

Rendered fromtutorial-100-posterior-predictive-checks.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Prior predictive checks

Rendered fromtutorial-070-prior-predictive-checks.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Quick start

Rendered fromtutorial-010-quick-start.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2018-06-21

Setting steady-state compartments

Rendered fromtutorial-030-steady-state-comps.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2019-12-12

Testing parameter identifiability

Rendered fromtutorial-130-parameter-identifiability.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-21

Units and priors

Rendered fromtutorial-060-units-priors.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2024-11-05
Started: 2020-05-07

Readme and manuals

Help Manual

Help pageTopics
The 'isotracer' packageisotracer-package isotracer
Subset method for 'networkModelStanfit' objects[.networkModelStanfit
Add fixed effects of one or several covariates to some parameters.add_covariates
Register a pulse event on one of the compartment of a topologyadd_pulse_event
A simple aquarium network model, ready to runaquarium_mod
An MCMC run from a simple aquarium network modelaquarium_run
Generic for as_tbl_graph()as_tbl_graph
Convert a network topology to a tbl_graphas_tbl_graph.topology
Convert a 'tidy_flows' object to an 'mcmc.list'as.mcmc.list.tidy_flows
Convert a 'tidy_steady_states' object to an 'mcmc.list'as.mcmc.list.tidy_steady_states
List the available priors for model parametersavailable_priors
Combine mcmc.list objectsc.mcmc.list
Calculate steady-state compartment sizes for a networkcalculate_steady_state
Return the compartments of a network modelcomps
Define a fixed-value priorconstant_p
Convert delta notation to proportion of heavy isotopedelta2prop
Calculate DIC from a model outputdic
Eelgrass phosphate incorporation data (McRoy & Barsdate 1970)eelgrass
Define an exponential priorexponential_p
Filter (alias for filter function from dplyr)filter
Filter a tibble based on the "group" columnfilter_by_group
Filter method for output of tidy_data_and_posterior_predict()filter.ppcNetworkModel
Pretty formatting of a 'prior' objectformat.prior
Pretty formatting of a 'prior_tibble' objectformat.prior_tibble
Define a gamma priorgamma_p
A quick-and-dirty way of visualizing relative flows in a networkggflows
Plot a topologyggtopo
Plot a network topologyggtopo.networkModel
Plot a topologyggtopo.topology
Get the grouping for a 'networkModel' objectgroups.networkModel
Define a half-Cauchy prior (on [0;+Inf])hcauchy_p
Dataset for nitrogren fluxes in a Trinidadian mountain stream (Collins 2016)lalaja
Protein degradation in Arabidopsis plants (Li et al. 2017)li2017 li2017_counts li2017_prots
Math generics for mcmc.list objectsMath.mcmc.list
Draw a heatmap based on the correlations between parametersmcmc_heatmap
Get a table with parameters which are missing priorsmissing_priors
Create an empty network modelnew_networkModel
Define a truncated normal prior (on [0;+Inf])normal_p
Function used for displaying 'prior' object in tibblesobj_sum.prior
Ops generics for 'mcmc.list' objectsOps.mcmc.list
Implementation of the '==' operator for priorsOps.prior
Ops generics for 'topology' objectsOps.topology
Return the parameters of a network modelparams
Function used for displaying 'prior' object in tibblespillar_shaft.prior
Plot observations/trajectories/predictions from a network modelplot.networkModel
Plot output from 'split_to_unit_plot'plot.ready_for_unit_plot
Draw from the posterior predictive distribution of the model outcomeposterior_predict
Draw from the posterior predictive distribution of the model outcomeposterior_predict.networkModelStanfit
Add a column with predictions from a fitpredict.networkModel
Print method for 'networkModel' objectsprint.networkModel
Pretty printing of a 'prior' objectprint.prior
Pretty printing of a 'prior_tibble' objectprint.prior_tibble
Pretty printing of a 'topology' objectprint.topology
Return the tibble containing the priors of a networkModelpriors
Calculate the trajectories of a network modelproject
Return the distribution family for observed proportionsprop_family
Convert isotopic proportions to delta valuesprop2delta
Draw a Sankey plot with basic defaultsquick_sankey
Run a MCMC sampler on a network model using Stanrun_mcmc
Generate samples from a network modelsample_from
Sample from a prior objectsample_from_prior
Sample parameter values from priorssample_params
Draw a Sankey plot for a network and estimated flowssankey
Define a beta prior (on [0;scale])scaled_beta_p
Select parameters based on their namesselect.mcmc.list
Set the half-life for radioactive tracersset_half_life
Set initial conditions in a network modelset_init
Set observations in a network modelset_obs
Set the parameters in a network modelset_params
Set prior(s) for a network modelset_prior set_priors
Set the distribution family for observed proportionsset_prop_family
Set the distribution family for observed sizesset_size_family
Flag some network compartments as being split compartmentsset_split
Flag some network compartments as being in a steady stateset_steady
Set the topology in a network model.set_topo
Return the distribution family for observed sizessize_family
Convert a Stanfit object to a nicely named mcmc.list objectstanfit_to_named_mcmclist
Extract data from a networkModel object into a tidy tibble.tidy_data
Prepare tidy data and posterior predictionstidy_dpp
Build a tidy table with the flows for each iterationtidy_flows
Extract a tidy output from an mcmc.listtidy_mcmc
Draw from the posterior predictive distribution of the model outcometidy_posterior_predict
Build a tidy table with the calculated steady states for each iterationtidy_steady_states
Build a tidy table with the trajectories for each iterationtidy_trajectories
Return the list of topologies, or a unique topology if all identicaltopo
Plot mcmc.list objectstraceplot
Network model for nitrogen fluxes in Trinidadian streams (Collins et al. 2016)trini_mod
Function used for displaying 'prior' object in tibblestype_sum.prior
Define a uniform prioruniform_p