[EMAIL PROTECTED] wrote:
Hello!
I have data containing a large number of probabilities (about 60) of
nonzero coefficients to predict 10 different independent variables (in
10 different BMA models). i've arranged these probabilities in a
matrix like so:
(IV1) (IV2) (IV3) ...
p(b0) p(b0) p(b0)
p(b1) p(b1) p(b1)
p(b2) p(b2) p(b2)
...
where p(b1) for independent variable 1 is p(b1 != 0) (given model
uncertainty - using the BMA package). i've also set it so that if the
coefficient is negative, the probability is listed as negative (to be
able to distinguish between significant positive and negative effects
by color).
i'd like to create a plot which is a 10x60 grid of rectangles, where
each rectangle is colored according to its probability of being
nonzero (preferably white would correspond to a zero probability).
i've looked into levelplot, heatmap, and image, and cant seem to get
exactly what im looking for.
heatmap gives me problems in that the output is inconsistent with the
data - among other things, the first and last rows do not seem to show
up (they are just white, despite clearly nonzero probabilities). even
if i do not use the dendrogram (Rowv and Colv set to NA), i still seem
to have an issue with a probability in a given row not corresponding
to the same color as the same probability in a different row.
levelplot seems to do exactly what i want it to do, except that i cant
find a way to label the individual columns and rows, which I really need
any ideas how to obtain the graph i want? Thanks!
Hi Nate,
Have a look at color2D.matplot, especially the last example.
Jim
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
