Package: isotracer 1.1.7

Matthieu Bruneaux

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.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://cran.r-universe.dev', 'https://cloud.r-project.org'))

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

4.92 score 60 scripts 650 downloads 61 exports 63 dependencies

Last updated 15 days agofrom:d8e8cbb122. Checks:OK: 1 WARNING: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Nov 06 2024
R-4.5-linux-x86_64	WARNING	Nov 06 2024

Exports:%>%add_covariates add_pulse_event as_tbl_graph as.mcmc.list available_priors calculate_steady_state comps constant_p delta2prop dic exponential_p filter filter_by_group gamma_p ggflows ggtopo groups hcauchy_p mcmc_heatmap missing_priors new_networkModel normal_p params posterior_predict priors project prop_family prop2delta quick_sankey run_mcmc sample_from sample_from_prior sample_params sankey scaled_beta_p select set_half_life set_init set_obs set_params set_prior set_priors set_prop_family set_size_family set_split set_steady set_topo size_family stanfit_to_named_mcmclist tidy_data tidy_dpp tidy_flows tidy_mcmc tidy_posterior_predict tidy_steady_states tidy_trajectories topo traceplot uniform_p varnames

Dependencies:abind backports BH callr checkmate cli coda colorspace cpp11 data.table desc distributional dplyr fansi farver generics ggplot2 glue gridExtra gtable inline isoband labeling latex2exp lattice lifecycle loo magrittr MASS Matrix matrixStats mgcv munsell nlme numDeriv pillar pkgbuild pkgconfig posterior processx ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan rstantools scales StanHeaders stringi stringr tensorA tibble tidyr tidyselect utf8 vctrs viridisLite withr

Calculating derived parameters

Rendered fromtutorial-110-derived-parameters.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-11-05
Started: 2021-09-27

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

Rendered fromcase-study-collins-2016.Rmdusingknitr::rmarkdownon Nov 06 2024.

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Defining pulse or drip events

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Handling replication

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How to simulate experiments

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Including fixed effects of covariates

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MCMC output format

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Post-run diagnostics and analyses

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Posterior predictive checks

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Prior predictive checks

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Quick start

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Setting steady-state compartments

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Testing parameter identifiability

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Units and priors

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Citation

Readme and manuals

Help Manual

Help page	Topics
The 'isotracer' package	isotracer-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 topology	add_pulse_event
A simple aquarium network model, ready to run	aquarium_mod
An MCMC run from a simple aquarium network model	aquarium_run
Generic for as_tbl_graph()	as_tbl_graph
Convert a network topology to a tbl_graph	as_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 parameters	available_priors
Combine mcmc.list objects	c.mcmc.list
Calculate steady-state compartment sizes for a network	calculate_steady_state
Return the compartments of a network model	comps
Define a fixed-value prior	constant_p
Convert delta notation to proportion of heavy isotope	delta2prop
Calculate DIC from a model output	dic
Eelgrass phosphate incorporation data (McRoy & Barsdate 1970)	eelgrass
Define an exponential prior	exponential_p
Filter (alias for filter function from dplyr)	filter
Filter a tibble based on the "group" column	filter_by_group
Filter method for output of tidy_data_and_posterior_predict()	filter.ppcNetworkModel
Pretty formatting of a 'prior' object	format.prior
Pretty formatting of a 'prior_tibble' object	format.prior_tibble
Define a gamma prior	gamma_p
A quick-and-dirty way of visualizing relative flows in a network	ggflows
Plot a topology	ggtopo
Plot a network topology	ggtopo.networkModel
Plot a topology	ggtopo.topology
Get the grouping for a 'networkModel' object	groups.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 objects	Math.mcmc.list
Draw a heatmap based on the correlations between parameters	mcmc_heatmap
Get a table with parameters which are missing priors	missing_priors
Create an empty network model	new_networkModel
Define a truncated normal prior (on [0;+Inf])	normal_p
Function used for displaying 'prior' object in tibbles	obj_sum.prior
Ops generics for 'mcmc.list' objects	Ops.mcmc.list
Implementation of the '==' operator for priors	Ops.prior
Ops generics for 'topology' objects	Ops.topology
Return the parameters of a network model	params
Function used for displaying 'prior' object in tibbles	pillar_shaft.prior
Plot observations/trajectories/predictions from a network model	plot.networkModel
Plot output from 'split_to_unit_plot'	plot.ready_for_unit_plot
Draw from the posterior predictive distribution of the model outcome	posterior_predict
Draw from the posterior predictive distribution of the model outcome	posterior_predict.networkModelStanfit
Add a column with predictions from a fit	predict.networkModel
Print method for 'networkModel' objects	print.networkModel
Pretty printing of a 'prior' object	print.prior
Pretty printing of a 'prior_tibble' object	print.prior_tibble
Pretty printing of a 'topology' object	print.topology
Return the tibble containing the priors of a networkModel	priors
Calculate the trajectories of a network model	project
Return the distribution family for observed proportions	prop_family
Convert isotopic proportions to delta values	prop2delta
Draw a Sankey plot with basic defaults	quick_sankey
Run a MCMC sampler on a network model using Stan	run_mcmc
Generate samples from a network model	sample_from
Sample from a prior object	sample_from_prior
Sample parameter values from priors	sample_params
Draw a Sankey plot for a network and estimated flows	sankey
Define a beta prior (on [0;scale])	scaled_beta_p
Select parameters based on their names	select.mcmc.list
Set the half-life for radioactive tracers	set_half_life
Set initial conditions in a network model	set_init
Set observations in a network model	set_obs
Set the parameters in a network model	set_params
Set prior(s) for a network model	set_prior set_priors
Set the distribution family for observed proportions	set_prop_family
Set the distribution family for observed sizes	set_size_family
Flag some network compartments as being split compartments	set_split
Flag some network compartments as being in a steady state	set_steady
Set the topology in a network model.	set_topo
Return the distribution family for observed sizes	size_family
Convert a Stanfit object to a nicely named mcmc.list object	stanfit_to_named_mcmclist
Extract data from a networkModel object into a tidy tibble.	tidy_data
Prepare tidy data and posterior predictions	tidy_dpp
Build a tidy table with the flows for each iteration	tidy_flows
Extract a tidy output from an mcmc.list	tidy_mcmc
Draw from the posterior predictive distribution of the model outcome	tidy_posterior_predict
Build a tidy table with the calculated steady states for each iteration	tidy_steady_states
Build a tidy table with the trajectories for each iteration	tidy_trajectories
Return the list of topologies, or a unique topology if all identical	topo
Plot mcmc.list objects	traceplot
Network model for nitrogen fluxes in Trinidadian streams (Collins et al. 2016)	trini_mod
Function used for displaying 'prior' object in tibbles	type_sum.prior
Define a uniform prior	uniform_p

Usage by other packages (reverse dependencies)