simmr: quick start guide

Step 1: install simmr





Step 2: load in the data

Some geese isotope data is included with this package. Find where it is with:

system.file("extdata", "geese_data.xls", package = "simmr")

Load into R with:

if (!requireNamespace("readxl", quietly = TRUE)) {
    stop("readxl needed for this vignette to work. Please install it.",
      call. = FALSE)
path = system.file("extdata", "geese_data.xls", package = "simmr")
geese_data = lapply(excel_sheets(path), read_excel, path = path)

If you want to see what the original Excel sheet looks like you can run system(paste('open',path)).

We can now separate out the data into parts

targets = geese_data[[1]]
sources = geese_data[[2]]
TEFs = geese_data[[3]]
concdep = geese_data[[4]]

Step 3: load the data into simmr

geese_simmr = simmr_load(mixtures = as.matrix(targets[, 1:2]),
                         source_names = sources$Sources,
                         source_means = as.matrix(sources[,2:3]),
                         source_sds = as.matrix(sources[,4:5]),
                         correction_means = as.matrix(TEFs[,2:3]),
                         correction_sds = as.matrix(TEFs[,4:5]),
                         concentration_means = as.matrix(concdep[,2:3]),
                         group = as.factor(paste('Day', targets$Time)))

Step 4: plot the data

plot(geese_simmr, group = 1:8)

Step 5: run through simmr and check convergence

geese_simmr_out = simmr_mcmc(geese_simmr)
summary(geese_simmr_out, type = 'diagnostics',
        group = 1)

Check that the model fitted well:

posterior_predictive(geese_simmr_out, group = 5)

Step 6: look at the output

Look at the influence of the prior:


Look at the histogram of the dietary proportions:

plot(geese_simmr_out, type = 'histogram')
compare_groups(geese_simmr_out, groups = 1:4, 
               source_name = 'Enteromorpha')

For the many more options available to run and analyse output, see the main vignette via vignette('simmr')

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simmr documentation built on Feb. 27, 2021, 5:05 p.m.