MDSIC {bayMDS} | R Documentation |
compute and plot MDSIC
Description
compute and plot MDSIC, a Bayesian selection criterion,
given in Oh and Raftery (2001)
based on the output of the function bmds
Usage
MDSIC(x, plot = TRUE, ...)
Arguments
x |
an object of class |
plot |
TRUE/FALSE, if TRUE plot the number of dimensions versus MDSIC (default=TRUE) |
... |
arguments to be passed to methods |
Details
Notes
To compute MDSIC, output of the function bmds
for
min_p
=1 is needed for sequential calculation of MDSIC.
Value
a list of MDSIC
results
- mdsic
MDSIC, for p =1,..,max_p
- llike
log likelihood term in MDSIC, for p=1,...,max_p
- penalty
penalty term in MDSIC, for p=1,...,max_p
References
Oh, M-S., Raftery A.E. (2001). Bayesian Multidimensional Scaling and Choice of Dimension, Journal of the American Statistical Association, 96, 1031-1044.
Examples
data(cityDIST)
out <- bmds(cityDIST, min_p=1, max_p=5 )
MDSIC(out)
[Package bayMDS version 2.0 Index]