This can be used to provide justification for the chosen defaults as defined in literature and what creates a reasonable result for Fwoxy. Make sure to back-transform means and tau at the time step to correct units from inputs.

• Units in documentation for b parameter should be (cm/hr) / (m2/s2), update comments in model file, ebase function
• Change name of troc argument to something different, this really isn't troc, something like "number of time steps per day" or "nstepd"
• Allow flexibility in running the model up to n days as the basis of the for loop, this requires changing the input to troc (as it's currently listed) from 86400 to whatever ndays is supplied by the user. This will still give us one estimate for a, r, and b per iteration of the loop, but it is based on model iterations that account for the full length of data in n days. This is not the same as running the model as is and taking the average across n days (not informed by data).
• Check units for dDO in output, is it mmol/m3/d?
• Allow user to define range on priors for all, but especially b since it is very constrained
• Add ability to plot DO_obs vs DO_mod as diagnostic, calc other goodness of fit measures
• How do we accommodate missing data if not all measurements are available for the specified time step in interval, e.g., interpolate, calc interval on the fly?

For time series with multiple missing days, interp = TRUE with maxgap = 1e6 or some other large number must be used for ebase() to work. This will set the timestep consistently based on the value passed to interval. However, these large gaps will be estimated by ebase() and need to be removed from the output. The isinterp column added from ebase_prep() could be used to filter these days, but must not filter interpolated values for days that have data.

The ebase() function will not work if there are dangling days at the beginning or end of the input data. An obscure JAGS error will be returned to the console, something like this:

Error in { : 
  task 8 failed - "4 nodes produced errors; first error: 'names' attribute [1] must be the same length as the vector [0]"

The ebase_prep() function needs to include a fix to cut these dangling days and return a warning indicating these records are removed.

Use examples from Appalachicola and Fwoxy

There are cases where a researcher may want to estimate production and respiration with no air-sea diffusion, such as for a sonde that is located at the bottom of the water column. In the comparable ecometab() function from the WtRegDO package, this feature is accomplished by setting bott_stat=TRUE. It is possible to approximate the result using the following code, but it is clunky, and a dedicated option to remove air-sea diffusion would be more intuitive.

library(EBASE)
library(dplyr)
library(lubridate)
library(doParallel)

# get four days of data
dat <- exdat %>%
  filter(month(DateTimeStamp) == 6 & day(DateTimeStamp) %in% 1:4)

##
# run ebase with defaults

# setup parallel backend
cl <- makeCluster(2)
registerDoParallel(cl)

res <- ebase(dat, interval = 900, Z = 1.85, bprior=c(0, 0.001))

stopCluster(cl)

Should be similar to BASEmetab

Including required inputs, JAGS model, units for I/O

Have to install jags...

Replace arng, brng, and rvar with asd, bsd, and rsd, add arguments for amean, bmean, and rmean.