nof1.nma.run: Run the model using the nof1 object for (network)...
In jiabei-yang/nof1ins: N-of-1 study general analysis tool

This is the core function that runs the model in our program. Before running this function, we need to specify data, prior, JAGS code, etc. using nof1.nma.data.

nof1.nma.run(
  nof1,
  inits = NULL,
  n.chains = 3,
  max.run = 1e+05,
  setsize = 10000,
  n.run = 50000,
  conv.limit = 1.05,
  extra.pars.save = NULL
)

`nof1`	nof1 object created from `nof1.nma.data` function
`inits`	Initial values for the parameters being sampled. If left unspecified, program will generate reasonable initial values.
`n.chains`	Number of chains to run
`max.run`	Maximum number of iterations that user is willing to run. If the algorithm is not converging, it will run up to `max.run` iterations before printing a message that it did not converge
`setsize`	Number of iterations that are run between convergence checks. If the algorithm converges fast, user wouldn't need a big setsize. The number that is printed between each convergence checks is the gelman-rubin diagnostics and we would want that to be below the conv.limit the user specifies.
`n.run`	Final number of iterations that the user wants to store. If after the algorithm converges, user wants less number of iterations, we thin the sequence. If the user wants more iterations, we run extra iterations to reach the specified number of runs
`conv.limit`	Convergence limit for Gelman and Rubin's convergence diagnostic.
`extra.pars.save`	Parameters that user wants to save besides the default parameters saved. See code using `cat(nof1$code)` to see which parameters can be saved.