An internal function which takes an R list object containing informative prior information for a multilevel model and translates it into a concise vector object to be used in an MLwiN macro.
prior2macro(prior, D, fpart, nrand)A long vector is returned in the format of MLwiN macro language. This includes all the specified prior parameters.
An R list object containing prior information for a multilevel model. See `Details' below.
A character string specifying the type of distribution, which
can be one of 'Normal', 'Binomial', 'Poisson',
'Negbinom', 'Multinomial', 'Multivariate Normal',
or 'Mixed'
An R list containing the list of fixed part parameter labels.
An R list of lists, containing the number of random parameters at each level.
Zhang, Z., Charlton, C.M.J., Parker, R.M.A., Leckie, G., and Browne, W.J. (2016) Centre for Multilevel Modelling, University of Bristol.
The prior list can contain the following:
fixe: For the fixed parameters, if proper normal priors are used
for some parameters, a list of vectors of length two is provided, each of which
specifies the mean and the standard deviation. If not given, default ('flat' or 'diffuse')
priors are used for the parameters. The names used in the list should match those in the
model output.
rp<level number>: A list object specifying the Wishart or gamma prior for the
covariance matrix or scalar variance at the levels specified, e.g. rp1 for
level 1, rp2 for level 2, etc. Consists of: (1)
estimate -- a prior guess for the true value of the covariance matrix;
(2) size -- sample size for guess.
Note that this is a weakly-informative prior and the default prior
is used if missing.
runMLwiN