prior.meta {BayesCACE}R Documentation

The function returns a custom string that specifies part of the model.


This function returns a partially complete prior string. Used internally - cannot be directly used.


prior.meta(random.effects = list(), re.values = list())



a list of logical values indicating whether random effects are included in the model. The list should contain the assignment for these parameters only: delta.n (\delta_{in}), delta.a (\delta_{ia}), delta.u (\delta_{iu}), delta.v (\delta_{iv}), delta.s (\delta_{is}), delta.b (\delta_{ib}), cor. The list should be in the form of list(delta.a = FALSE, cor = FALSE, ...). By default, this is an empty list, and all parameters are default to TRUE. Parameters that are not listed in the list are assumed to be TRUE. Note that \rho (cor) can only be included when both \delta_{in} (delta.n) and \delta_{ia} (delta.a) are set to TRUE. Otherwise, a warning occurs and the model continues running by forcing delta.n = TRUE and delta.a = TRUE.


a list of parameter values for the random effects. It should contain the assignment for these parameters only: alpha.n.m and alpha.n.s, which refer to the mean and standard deviation used in the normal distribution estimation of alpha.n, as well as alpha.a.m, alpha.a.s, alpha.s.m, alpha.s.s, alpha.b.m, alpha.b.s, alpha.u.m, alpha.u.s, alpha.v.m, alpha.v.s. It also contains the shape and rate parameters of the gamma distributions of the standard deviation variable of delta.n, delta.a, delta.u, delta.v delta.s, delta.b. The shape parameters are named as tau.n.h and tau.a.h, for example, and the rate parameters are named as tau.n.r and tau.a.r. You do not need to specify the shape and rate parameters if the corresponding random effect is set to FALSE in random.effects, since they will not be used anyways. By default, re.values is an empty list, and all the mean are set to 0, and alpha.n.s = alpha.a.s = 0.16, and alpha.s.s = alpha.b.s = alpha.u.s = alpha.v.s = 0.25, and the shape and rate parameters are default to 2.


custom prior string


model.string <- prior.meta()

[Package BayesCACE version 1.2.1 Index]