ACF Plots for missmodel objects

DESCRIPTION:

Produces ACF plots for missmodel objects produced by data augmentation. These may be used to help diagnose convergence of a data augmentation algorithm.

If cross correlations are desired, use the function acf and/or acf.plot directly.

USAGE:

daAcfPlot(da.missmod, subset = 1:100, lag.max = 100,
          select = F, variables = (all), ask = T, ...) 

REQUIRED ARGUMENTS:

da.missmod
class "missmodel" object produced by a data augmentation algorithm.

OPTIONAL ARGUMENTS:

subset
vector specifying which subset of the rows of the parameter iterates (in the paramIter component of the missmodel object) should be used to calculate autocorrelations. This can be a logical vector (which is replicated to have length equal to the number of rows), a numeric vector indicating the observation numbers to be included, or a character vector of the row names to be included. The subset should specify a consecutive set of iterates.
lag.max
the maximum number of lags at which to estimate the autocovariance. This is the corresponding argument to the function acf
select
logical flag: if TRUE, you may select the variables (parameters) to plot. If FALSE, variables indicated by the variables argument are plotted.
variables
vector of indices of variables to plot. By default all are plotted.
ask
logical flag: if TRUE, you must hit the return key between pages. This allows you to inspect each graph when the graphics device does not stop automatically between pages.

SIDE EFFECTS:

For all or selected parameters: produce an autocorrelation function plot.

REFERENCES:

Schafer, J. L. (1997), Analysis of Incomplete Multivariate Data, Chapman & Hall, London.

SEE ALSO:

, , , .

EXAMPLES:

crime.DA <- daLoglin(crime, margins = count~Visit.1:Visit.2,  
                     control = list(save = 101:500)) 
daAcfPlot(crime.DA) 
# plot the last 2 parameters
daAcfPlot(crime.DA, variables = 3:4)
# plot the first 3 parameters, interactively
daAcfPlot(crime.DA, select = T) 
Select Variable Indices (or 0 to exit): 
 1 Visit.1=1;Visit.2=1 
 2 Visit.1=2;Visit.2=1 
 3 Visit.1=1;Visit.2=2 
 4 Visit.1=2;Visit.2=2 
? 1:3