Usage
write.MCMC(indata, dtafile, oldsyntax = FALSE, resp, levID, expl, rp,
D = "Normal", nonlinear = c(0, 1), categ = NULL, notation = NULL,
nonfp = NULL, clre = NULL, Meth = 1, merr = NULL, carcentre = FALSE,
maxiter = 20, convtol = 2, seed = 1, iterations = 5000,
burnin = 500, scale = 5.8, thinning = 1, priorParam = "default",
refresh = 50, fixM = 1, residM = 1, Lev1VarM = 1, OtherVarM = 1,
adaption = 1, priorcode = 1, rate = 50, tol = 10, lclo = 0,
mcmcOptions, fact = NULL, xc = NULL, mm = NULL, car = NULL,
BUGO = NULL, mem.init = "default", optimat = FALSE, modelfile, initfile,
datafile, macrofile, IGLSfile, MCMCfile, chainfile, MIfile, resifile,
resi.store = FALSE, resioptions, resichains, FACTchainfile,
resi.store.levs = NULL, debugmode = FALSE, startval = NULL,
dami = NULL, namemap = sapply(colnames(indata), as.character))
Arguments
indata
A data.frame object containing the data to be modelled.
dtafile
The file name of the dataset to be imported into MLwiN, which
is in Stata format (i.e. with extension .dta).
oldsyntax
Specified as FALSE if new syntax has been used in
Formula object, else specified as TRUE (to enable
backcompatibility).
resp
A character string (vector) of response variable(s).
levID
A character string (vector) of the specified level ID(s). The
ID(s) should be sorted in the descending order of levels (e.g.
levID = c('level2', 'level1') where 'level2' is the higher
level).
expl
A character string (vector) of explanatory (predictor)
variable(s).
rp
A character string (vector) of random part of random variable(s).
D
A character string/vector specifying the type of distribution to be modelled, which
can include 'Normal' (the default), 'Binomial', 'Poisson',
'Unordered Multinomial', 'Ordered Multinomial'
nonlinear
A character vector specifying linearisation method for IGLS
starting values for discrete
response models (see Chapter 9 of Rasbash et al 2012, and Goldstein 2011).
N = 0 specifies marginal quasi-likelihood
linearization (MQL), whilst
categ
Specifies categorical variable(s) as a matrix. Each column
corresponds to a categorical variable; the first row specifies the name(s)
of variable(s); the second row specifies the name(s) of reference group(s),
NA(s) if no reference group;
notation
Specifies the model subscript notation to be used in the
MLwiN equations window. 'class' means no multiple subscripts, whereas
'level' has multiple subscripts.
nonfp
Removes the fixed part of random variable(s). NA if no
variable is removed.
clre
A matrix used to estimate some, but not all, of the variances
and covariances for a set of coefficients at a particular level. Remove from
the random part at level the covariance matrix element(s)
defined by the pair(s) of rows
Meth
Specifies the maximum likelihood estimation method to be used
when generating starting values via (R)IGLS.
If Meth = 0 estimation method is set to RIGLS. If Meth = 1
estimation method is set to IGLS (the default setting). If <
merr
A vector which sets-up measurement errors on predictor
variables. The first element N defines the number of variables that
have measurement errors. Then, for each variable with measurement error, a
pair of inputs is required: the first of
carcentre
If CAR model (i.e. if car is non-NULL),
carcentre = TRUE mean-centres all random effects at that level.
maxiter
When generating starting values via (R)IGLS, a numeric
value specifying the total number of iterations, from
the start, before IGLS estimation halts (if startval = NULL).
convtol
When generating starting values via (R)IGLS, a numeric
value specifying the IGLS convergence criterion, as
specified in the tol option within estoptions, where
startval = NULL) (see
seed
An integer specifying the random seed in MLwiN.
iterations
An integer specifying the number of iterations after
burn-in.
burnin
An integer specifying length of the burn-in.
scale
An integer specifying the scale factor of proposed variances;
this number will be multiplied by the estimated
parameter variance (from IGLS/RIGLS) to give the proposal distribution variance.
thinning
An integer specifying the frequency with which successive
values in the Markov chain are stored. By default thinning = 1.
priorParam
A vector specifying the informative priors used, as output
from prior2macro. refresh
An integer specifying how frequently the parameter estimates
are refreshed on the screen during iterations; only applies if
debugmode = TRUE in estoptions:
see runMLwiN. fixM
Specifies the fixed effect method: 1 for Gibbs Sampling,
2 for univariate MH Sampling and 3 for multivariate MH
Sampling.
residM
Specifies the residual method: 1 for Gibbs Sampling,
2 for univariate MH Sampling and 3 for multivariate MH
Sampling.
Lev1VarM
Specifies the level 1 variance method: 1 for Gibbs
Sampling, 2 for univariate MH Sampling and 3 for multivariate
MH Sampling.
OtherVarM
Specifies the variance method for other levels: 1
for Gibbs Sampling, 2 for univariate MH Sampling and 3 for
multivariate MH Sampling.
adaption
adaption = 1 indicates adaptation is to be used;
0 otherwise.
priorcode
An integer indicating which default priors are to be used
for the variance parameters. This parameter takes the value 1 for
Gamma priors or 0 for Uniform on the variance scale priors. See the
section on 'Priors' in the MLwiN h
rate
An integer specifying the acceptance rate (as a percentage);
this command is ignored if adaption = 0.
tol
An integer specifying tolerance (as a percentage) for the acceptance rate.
lclo
This command toggles on/off the possible forms of complex level
1 variation when using MCMC. lclo = 0 expresses the level
1 variation as a function of the predictors, whereas lclo = 1 expresses the
log of the level 1 precision
mcmcOptions
A list of other MCMC options used. See `Details' below.
fact
A list of objects specified for factor analysis. See `Details'
below.
xc
Indicates whether model is cross-classified (TRUE) or
nested (FALSE). xc = NULL by default (corresponding to
FALSE), unless either mm or car are not null, in
which case
mm
Specifies the structure of a multiple membership model.
Can be a list of variable names, a list of vectors, or a matrix (e.g. see
df2matrix). In the case of the former, each
element of the list corresp car
A list specifying structure of a conditional autoregressive (CAR)
model. Each element of the list corresponds to a level (classification) of
the model, in descending order. If a level is not a spatial classification,
then NA is specified.
BUGO
If non-NULL uses BUGS for MCMC estimation using files
specified in modelfile, initfile and datafile.
mem.init
A vector which sets and displays worksheet capacities for
the current MLwiN session according to the value(s) specified. By default,
the number of levels is nlev+1; worksheet size in thousands of cells
is 6000; the number of columns is 250
optimat
This option instructs MLwiN to limit the maximum matrix size
that can be allocated by the (R)IGLS algorithm. Specify optimat = TRUE
if MLwiN gives the following error message 'Overflow allocating smatrix'.
This error message arises if one
modelfile
A file name where the BUGS model will be saved in .txt
format.
initfile
A file name where the BUGS initial values will be saved
in .txt format.
datafile
A file name where the BUGS data will be saved in .txt
format.
macrofile
A file name where the MLwiN macro file will be saved.
IGLSfile
A file name where the IGLS estimates will be saved.
MCMCfile
A file name where the MCMC estimates will be saved.
chainfile
A file name where the MCMC chains will be saved.
MIfile
A file name where the missing values will be saved.
resifile
A file name where the residual estimates will be saved.
resi.store
A logical value to indicate if residuals are to be stored
(TRUE) or not (FALSE).
resioptions
A string vector to specify the various residual options.
The 'variance' option calculates the posterior variances instead of
the posterior standard errors; the 'standardised' option calculates standardised
residuals.
resichains
A file name where the residual chains will be saved.
FACTchainfile
A file name where the factor chains will be saved.
resi.store.levs
An integer vector indicating the levels at which the
residual chains are to be stored.
debugmode
A logical value determining whether MLwiN is run in the
background or not. The default value is FALSE: i.e. MLwiN is run in
the background. If TRUE the MLwiN GUI is opened, and then pauses after the model
has been set-up, allo
startval
A list of numeric vectors specifying the starting values
when using MCMC. FP.b corresponds to the estimates for the fixed
part; FP.v specifies the variance/covariance estimates for the fixed
part; RP.b specifies t
dami
This command outputs a complete (i.e. including non-missing
responses) response variable y. If dami = c(0, , ,...) then
the response variables returned will be the value of y at the iterations
quoted (as integers
namemap
A mapping of column names to DTA friendly shorter names