Summarizing distributions of parameters simulated from statistical age models using a Markov Chain Monte Carlo method.
reportMC(obj, burn = 10000, thin = 5,
plot = TRUE, outfile = NULL, ...)Return a list that contains the following elements:
means, standard deviations, and modes of simulated parameters
quantiles of simulated parameters
maximum logged likelihood values calculated using the means and modes of simulated parameters
Bayesian Information Criterion (BIC) values calculated using the means and modes of simulated parameters
list(required): an object of S3 class "mcAgeModels", which is produced by function mcFMM or mcMAM
integer(with default): number of iterations (i.e., the initial, non-stationary
portion of the chain) to be discarded
integer(with default): take every thin-th iteration
logical(with default): plot the MCMC output or not
character(optional): if specified, simulated parameters will be written to a CSV file named "outfile" and saved to the current work directory
do not use
Function reportMC summarizes the output of a Markov Chain (the mean values, the standard deviations, the mode values, and the 2.5, 25, 50, 75, 97.5 quantiles of the simulated parameters). The initial i (burn=i) samples may have been affected by the inital state and has to be discarded ("burn-in"). Autocorrelation of simulated samples can be reduced by taking every j-th (thin=j) iteration ("thining").
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Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB, 2013. Bayesian data analysis. Chapman & Hall/CRC Press.
Peng J, Dong ZB, Han FQ, 2016. Application of slice sampling method for optimizing OSL age models used for equivalent dose determination. Progress in Geography, 35(1): 78-88. (In Chinese).
mcFMM; mcMAM