I'm not sure if this is appropriate. If the sum of your variables is
always the same constant, then you might try a Ternary plot (
http://en.wikipedia.org/wiki/Ternary_plot ).
The "vcd" package can make ternary plots.
On 01/20/2012 02:56 PM, Roary wrote:
I have two observed categorical variables X1 and X2, with X3=X1+X2, and a
continuous response Y. I can interpolate the surface and construct an
ordinary 2D square contour plot (with X1,X2 axes and X3 on the diagonal).
However, I would like to change the orientation of the plot so that the
axes fit a parallelogram shaped grid made up from triangles. This would
place X3 on the same scale as X1 and X2 and allow for an easier
interpretation of the data for my research question.
I hope this makes more sense! Thanks, Roary.
Uwe Ligges-3 wrote
Not sure if I understand the question: If you have more data the grid
produced by image() or contour() will be finer anyway...
Perhaps we just need an example what you are actually asking for.
Uwe Ligges
On 20.01.2012 13:28, Roary wrote:
Hi All,
I have 3 variables which present a perfect linear dependency such that
the
third is the sum of the first two. I have an ordinary 2D contour plot on
a
square grid with the first two variables forming the axes and the third
naturally being the diagonals. From an interpretive point of view it
would
be nice to plot these two variables on a finer grid such that the third
can
have the same scaling (i.e. a finer grid) as the first two and this would
look better on a triangular mesh. Is this possible in R?
Many thanks,
Roary
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