# Isotopic Tracer Analysis Using MCMC

## Documentation for package ‘isotracer’ version 1.1.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

isotracer-package | The 'isotracer' package
add_covariates | Add fixed effects of one or several covariates to some parameters.
add_pulse_event | Register a pulse event on one of the compartment of a topology
aquarium_mod | A simple aquarium network model, ready to run
aquarium_run | An MCMC run from a simple aquarium network model
as.mcmc.list.tidy_flows | Convert a 'tidy_flows' object to an 'mcmc.list'
as.mcmc.list.tidy_steady_states | Convert a 'tidy_steady_states' object to an 'mcmc.list'
as_tbl_graph | Generic for as_tbl_graph()
as_tbl_graph.topology | Convert a network topology to a tbl_graph
available_priors | List the available priors for model parameters
c.mcmc.list | Combine mcmc.list objects
calculate_steady_state | Calculate steady-state compartment sizes for a network
comps | Return the compartments of a network model
constant_p | Define a fixed-value prior
delta2prop | Convert delta notation to proportion of heavy isotope
dic | Calculate DIC from a model output
eelgrass | Eelgrass phosphate incorporation data (McRoy & Barsdate 1970)
exponential_p | Define an exponential prior
filter | Filter (alias for filter function from dplyr)
filter.ppcNetworkModel | Filter method for output of tidy_data_and_posterior_predict()
filter_by_group | Filter a tibble based on the "group" column
format.prior | Pretty formatting of a 'prior' object
format.prior_tibble | Pretty formatting of a 'prior_tibble' object
gamma_p | Define a gamma prior
ggflows | A quick-and-dirty way of visualizing relative flows in a network
ggtopo | Plot a topology
ggtopo.networkModel | Plot a network topology
ggtopo.topology | Plot a topology
groups.networkModel | Get the grouping for a 'networkModel' object
hcauchy_p | Define a half-Cauchy prior (on [0;+Inf])
isotracer | The 'isotracer' package
lalaja | Dataset for nitrogren fluxes in a Trinidadian mountain stream (Collins 2016)
li2017 | Protein degradation in Arabidopsis plants (Li et al. 2017)
li2017_counts | Protein degradation in Arabidopsis plants (Li et al. 2017)
li2017_prots | Protein degradation in Arabidopsis plants (Li et al. 2017)
Math.mcmc.list | Math generics for mcmc.list objects
mcmc_heatmap | Draw a heatmap based on the correlations between parameters
missing_priors | Get a table with parameters which are missing priors
new_networkModel | Create an empty network model
normal_p | Define a truncated normal prior (on [0;+Inf])
obj_sum.prior | Function used for displaying 'prior' object in tibbles
Ops.mcmc.list | Ops generics for 'mcmc.list' objects
Ops.prior | Implementation of the '==' operator for priors
Ops.topology | Ops generics for 'topology' objects
params | Return the parameters of a network model
pillar_shaft.prior | Function used for displaying 'prior' object in tibbles
plot.networkModel | Plot observations/trajectories/predictions from a network model
plot.ready_for_unit_plot | Plot output from 'split_to_unit_plot'
posterior_predict | Draw from the posterior predictive distribution of the model outcome
posterior_predict.networkModelStanfit | Draw from the posterior predictive distribution of the model outcome
predict.networkModel | Add a column with predictions from a fit
print.networkModel | Print method for 'networkModel' objects
print.prior | Pretty printing of a 'prior' object
print.prior_tibble | Pretty printing of a 'prior_tibble' object
print.topology | Pretty printing of a 'topology' object
priors | Return the tibble containing the priors of a networkModel
project | Calculate the trajectories of a network model
prop_family | Return the distribution family for observed proportions
quick_sankey | Draw a Sankey plot with basic defaults
run_mcmc | Run a MCMC sampler on a network model using Stan
sample_from | Generate samples from a network model
sample_from_prior | Sample from a prior object
sample_params | Sample parameter values from priors
sankey | Draw a Sankey plot for a network and estimated flows
scaled_beta_p | Define a beta prior (on [0;scale])
select.mcmc.list | Select parameters based on their names
set_half_life | Set the half-life for radioactive tracers
set_init | Set initial conditions in a network model
set_obs | Set observations in a network model
set_params | Set the parameters in a network model
set_prior | Set prior(s) for a network model
set_priors | Set prior(s) for a network model
set_prop_family | Set the distribution family for observed proportions
set_size_family | Set the distribution family for observed sizes
set_split | Flag some network compartments as being split compartments
set_steady | Flag some network compartments as being in a steady state
set_topo | Set the topology in a network model.
size_family | Return the distribution family for observed sizes
stanfit_to_named_mcmclist | Convert a Stanfit object to a nicely named mcmc.list object
tidy_data | Extract data from a networkModel object into a tidy tibble.
tidy_dpp | Prepare tidy data and posterior predictions
tidy_flows | Build a tidy table with the flows for each iteration
tidy_mcmc | Extract a tidy output from an mcmc.list
tidy_posterior_predict | Draw from the posterior predictive distribution of the model outcome
tidy_steady_states | Build a tidy table with the calculated steady states for each iteration
tidy_trajectories | Build a tidy table with the trajectories for each iteration
topo | Return the list of topologies, or a unique topology if all identical
traceplot | Plot mcmc.list objects
trini_mod | Network model for nitrogen fluxes in Trinidadian streams (Collins et al. 2016)
type_sum.prior | Function used for displaying 'prior' object in tibbles
uniform_p | Define a uniform prior
[.networkModelStanfit | Subset method for 'networkModelStanfit' objects