On 01/21/2012 09:38 PM, Roary wrote:
Thanks for your responses Jason and Jim. The ternary plot is definitely the
right style with the triangle fill. However, one of the important features
(that perhaps I understated) is that X3 will have more categories than X1
and X2, therefore the triangular sh
Thanks for your responses Jason and Jim. The ternary plot is definitely the
right style with the triangle fill. However, one of the important features
(that perhaps I understated) is that X3 will have more categories than X1
and X2, therefore the triangular shape is not appropriate. If X1 has I
cat
On 01/20/2012 11:28 PM, 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
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 variab
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
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 lin
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
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