mcmc.operators: Operator parameters that control the operation of the MCMC

Description Usage Format Details Examples


These parameters, which are passed to the MCMC and MCMC_BB functions, control the operation of the MCMC. They specify the number of generations over which the MCMC runs; the scales of the tuning parameters (stp) for all parameters updated via random-walk samplers; the save, print, and sample frequency of the chain, and the output file names.




The format is: List of 12

$ delta :

num 0.001

$ aD_stp :

num 0.0018

$ aE_stp :

num 0.04

$ a2_stp :

num 0.0035

$ phi_stp :

num 30

$ thetas_stp:

num 0.07

$ mu_stp :

num 0.17

$ ngen :

num 100

$ printfreq :

num 2

$ savefreq :

num 100

$ samplefreq:

num 5

$ prefix :

chr "example_"



The size of the "delta shift" on the off-diagonal elements of the parametric covariance matrix, used to ensure its positive-definiteness (even, for example, when there are separate populations sampled at the same geographic/ecological coordinates). This value must be large enough that the covariance matrix is positive-definite, but, if possible, should be smaller than the smallest off-diagonal distance elements, lest it have an undue impact on inference. If the user is concerned that the delta shift is too large relative to the pairwise distance elements in D and E, she should run subsequent analyses, varying the size of delta, to see if it has an impact on model inference.


The scale of the tuning parameter on aD (alphaD). The scale of the tuning parameter is the standard deviation of the normal distribution from which small perturbations are made to those parameters updated via a random-walk sampler. A larger value of the scale of the tuning parameter will lead to, on average, larger proposed moves and lower acceptance rates (for more on acceptance rates, see plot_acceptance_rate).


The scale of the tuning parameter on aE (alphaE). If there are multiple ecological distances included in the analysis, there will be multiple alphaE parameters (one for each matrix in the list of E). These may be updated all with the same scale of a tuning parameter, or they can each get their own, in which case aE_stp should be a vector of length equal to the number of ecological distance variables.


The scale of the tuning parameter on a2 (alpha_2).


The scale of the tuning parameter on the phi parameters.


The scale of the tuning parameter on the theta parameters.


The scale of the tuning parameter on mu.


The number of generations over which to run the MCMC (one parameter is updated at random per generation, with mu, theta, and phi all counting, for the purposes of updates, as one parameter).


The frequency with which MCMC progress is printed to the screen. If printfreq =1000, an update with the MCMC generation number and the posterior probability at that generation will print to the screen every 1000 generations.


The frequency with which the MCMC saves its output as an R object (savefreq =50,000 means that MCMC output is saved every 50,000 generations). If ngen is large, this saving process may be computationally expensive, and so should not be performed too frequently. However, users may wish to evalute MCMC performance while the chain is still running, or may be forced to truncate runs early, and should therefore specify a savefreq that is less than ngen. We recommend a savefreq of between 1/10th and 1/20th of ngen.


The thinning of the MCMC chain (samplefreq = 1000 means that the parameter values saved in the MCMC output are sampled once every 1000 generations). A higher samplefreq will decrease parameter autocorrelation time. However, there is still information in autocorrelated draws from the joint posterior, so the samplefreq should be viewed merely as a computational convenience, to decrease the size of the MCMC output objects.


If specified, this prefix will be added to all output file names.


## see \command{MCMC} and \command{MCMC_BB} for example usage.

BEDASSLE documentation built on May 2, 2019, 6:10 a.m.