Some geese isotope data is included with this package. Find where it is with:
Load into R with:
library(readxl)
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
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)))
simmr
and check convergenceCheck that the model fitted well:
## Compiling model graph
## Resolving undeclared variables
## Allocating nodes
## Graph information:
## Observed stochastic nodes: 40
## Unobserved stochastic nodes: 46
## Total graph size: 190
##
## Initializing model
Look at the influence of the prior:
Look at the histogram of the dietary proportions:
## Most popular orderings are as follows:
## Probability
## Day 428 > Day 124 > Day 398 > Day 1 0.2192
## Day 428 > Day 398 > Day 124 > Day 1 0.1661
## Day 428 > Day 124 > Day 1 > Day 398 0.1567
## Day 428 > Day 398 > Day 1 > Day 124 0.1094
## Day 428 > Day 1 > Day 124 > Day 398 0.0769
## Day 428 > Day 1 > Day 398 > Day 124 0.0761
## Day 124 > Day 428 > Day 398 > Day 1 0.0525
## Day 398 > Day 428 > Day 124 > Day 1 0.0356
## Day 124 > Day 428 > Day 1 > Day 398 0.0297
## Day 398 > Day 428 > Day 1 > Day 124 0.0197
## Day 398 > Day 124 > Day 428 > Day 1 0.0133
## Day 124 > Day 398 > Day 428 > Day 1 0.0122
## Day 1 > Day 428 > Day 124 > Day 398 0.0078
## Day 1 > Day 428 > Day 398 > Day 124 0.0056
## Day 124 > Day 398 > Day 1 > Day 428 0.0036
## Day 124 > Day 1 > Day 428 > Day 398 0.0031
## Day 1 > Day 124 > Day 428 > Day 398 0.0025
## Day 398 > Day 1 > Day 428 > Day 124 0.0022
## Day 124 > Day 1 > Day 398 > Day 428 0.0019
## Day 398 > Day 124 > Day 1 > Day 428 0.0017
## Day 1 > Day 398 > Day 428 > Day 124 0.0014
## Day 398 > Day 1 > Day 124 > Day 428 0.0014
## Day 1 > Day 398 > Day 124 > Day 428 0.0011
## Day 1 > Day 124 > Day 398 > Day 428 0.0003
For the many more options available to run and analyse output, see the main vignette via vignette('simmr')