## ---- eval=FALSE-------------------------------------------------------------- # library(MixSIAR) # mixsiar.dir <- find.package("MixSIAR") # paste0(mixsiar.dir,"/example_scripts") ## ---- eval=FALSE-------------------------------------------------------------- # source(paste0(mixsiar.dir,"/example_scripts/mixsiar_script_wolves.R")) ## ----------------------------------------------------------------------------- library(MixSIAR) ## ----------------------------------------------------------------------------- # Replace the system.file call with the path to your file mix.filename <- system.file("extdata", "wolves_consumer.csv", package = "MixSIAR") # Load the mixture/consumer data mix <- load_mix_data(filename=mix.filename, iso_names=c("d13C","d15N"), factors=c("Region","Pack"), fac_random=c(TRUE,TRUE), fac_nested=c(FALSE,TRUE), cont_effects=NULL) ## ----------------------------------------------------------------------------- # Replace the system.file call with the path to your file source.filename <- system.file("extdata", "wolves_sources.csv", package = "MixSIAR") # Load the source data source <- load_source_data(filename=source.filename, source_factors="Region", conc_dep=FALSE, data_type="means", mix) ## ----------------------------------------------------------------------------- # Replace the system.file call with the path to your file discr.filename <- system.file("extdata", "wolves_discrimination.csv", package = "MixSIAR") # Load the discrimination/TDF data discr <- load_discr_data(filename=discr.filename, mix) ## ---- eval=FALSE-------------------------------------------------------------- # # Make an isospace plot # plot_data(filename="isospace_plot", plot_save_pdf=TRUE, plot_save_png=FALSE, mix,source,discr) ## ----------------------------------------------------------------------------- # Calculate the convex hull area, standardized by source variance calc_area(source=source,mix=mix,discr=discr) ## ---- eval=FALSE-------------------------------------------------------------- # # default "UNINFORMATIVE" / GENERALIST prior (alpha = 1) # plot_prior(alpha.prior=1,source) ## ---- eval=FALSE-------------------------------------------------------------- # # Write the JAGS model file # model_filename <- "MixSIAR_model.txt" # Name of the JAGS model file # resid_err <- TRUE # process_err <- TRUE # write_JAGS_model(model_filename, resid_err, process_err, mix, source) ## ---- eval=FALSE-------------------------------------------------------------- # run <- list(chainLength=200000, burn=150000, thin=50, chains=3, calcDIC=TRUE) ## ---- eval=FALSE-------------------------------------------------------------- # jags.1 <- run_model(run="test", mix, source, discr, model_filename) ## ---- eval=FALSE-------------------------------------------------------------- # jags.1 <- run_model(run="normal", mix, source, discr, model_filename) ## ---- eval=FALSE-------------------------------------------------------------- # output_options <- list(summary_save = TRUE, # summary_name = "summary_statistics", # sup_post = FALSE, # plot_post_save_pdf = TRUE, # plot_post_name = "posterior_density", # sup_pairs = FALSE, # plot_pairs_save_pdf = TRUE, # plot_pairs_name = "pairs_plot", # sup_xy = TRUE, # plot_xy_save_pdf = FALSE, # plot_xy_name = "xy_plot", # gelman = TRUE, # heidel = FALSE, # geweke = TRUE, # diag_save = TRUE, # diag_name = "diagnostics", # indiv_effect = FALSE, # plot_post_save_png = FALSE, # plot_pairs_save_png = FALSE, # plot_xy_save_png = FALSE, # diag_save_ggmcmc = FALSE) ## ---- eval=FALSE-------------------------------------------------------------- # output_JAGS(jags.1, mix, source, output_options)