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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_small.xls", package = "cosimmr")
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]]
Note that if you don’t have TEFs or concentration dependence you can just leave them blank in the step below.
cosimmr
Here we are using Weight as a covariate. data are inputted as matrices
Weight <- targets$`Net Wt`
geese_cosimmr <- cosimmr_load(
formula = as.matrix(targets[, 1:2]) ~ Weight,
source_names = sources$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])
)
##Step 5: Run through cosimmr
##Step 5: Look at the output Look at the influence of the prior:
Look at the histogram of the dietary proportions for observations 1 and 2:
For the many more options available to run and analyse output, see
the main vignette via vignette('cosimmr')
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.