Plotting ProcD.lm results

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Hildur Magnúsdóttir

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Sep 6, 2017, 9:40:57 AM9/6/17
to geomorph R package
Hi all,

I am currently analysing the variation in my shape data using ProcD.lm(). My resulting model is shape~sex+longitude+substrate and the data is from several sites which differ in longitude and substrate type.

Is there any way to make a clear graph that display these results, as you would do for models with other types of data?

Regards,
Hildur

--
Hildur Magnúsdóttir
PhD Student in Biology
University of Iceland, Faculty of Life and Environmental Sciences
and Hólar University College, Department of Aquaculture and Fish Biology
Telephone: +354 823 2485

Mike Collyer

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Sep 6, 2017, 9:50:16 AM9/6/17
to geomorph-...@googlegroups.com
The plot.procD.lm function has both PC and regression plotting options.  There are some examples in the procD.lm help file.  As every model is unique, so are the plotting options.  The PC plot will rotate your data space to align with the major axes of shape variation, as estimated by your model; i.e., a PCA of predicted values with projection of the observed values onto the PC axes.  The regression plot is much like the allometry plots in procD.allometry, except one can use a predictor other than shape.

All par options available to the plot function can be used with the plots to tailor the plots any way you like.

Hope that helps!

Mike


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Hildur Magnúsdóttir

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Sep 11, 2017, 6:18:01 AM9/11/17
to geomorph R package
Thank you Mike!

Regards,
Hildur

On Wed, Sep 6, 2017 at 1:50 PM, Mike Collyer <mlco...@gmail.com> wrote:
The plot.procD.lm function has both PC and regression plotting options.  There are some examples in the procD.lm help file.  As every model is unique, so are the plotting options.  The PC plot will rotate your data space to align with the major axes of shape variation, as estimated by your model; i.e., a PCA of predicted values with projection of the observed values onto the PC axes.  The regression plot is much like the allometry plots in procD.allometry, except one can use a predictor other than shape.

All par options available to the plot function can be used with the plots to tailor the plots any way you like.

Hope that helps!

Mike


On Sep 6, 2017, at 9:40 AM, Hildur Magnúsdóttir <hibba...@gmail.com> wrote:

Hi all,

I am currently analysing the variation in my shape data using ProcD.lm(). My resulting model is shape~sex+longitude+substrate and the data is from several sites which differ in longitude and substrate type.

Is there any way to make a clear graph that display these results, as you would do for models with other types of data?

Regards,
Hildur

--
Hildur Magnúsdóttir
PhD Student in Biology
University of Iceland, Faculty of Life and Environmental Sciences
and Hólar University College, Department of Aquaculture and Fish Biology
Telephone: +354 823 2485

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