[R-sig-Geo] MADIFA results

[Mathieu Basille]

Dear Michela,

I apologize for the late answer. From the help of mahasuhab, section "Details":

?mahasuhab

      The function ‘mahasuhab’ first computes this mean vector as well
      as the variance-covariance matrix of the niche density function,
      based on the value of habitat variables in the sample of
      locations.  Then, the *squared* Mahalanobis distance from this
      optimum is computed for each pixel of the map.  Thus, the smaller
      this squared distance is for a given pixel, and the better is the
      habitat in this pixel.

      Assuming multivariate normality, squared Mahalanobis distances are
      approximately distributed as Chi-square with n-1 degrees of
      freedom, where n equals the number of habitat characteristics.  If
      the argument ‘type = "probability"’, maps of these p-values are
      returned by the function. As such these are the probabilities of a
      larger squared Mahalanobis distance than that observed when x is
      sampled from the niche.

Hope this helps!
Mathieu Basille.


Le 02/07/2013 04:29 AM, Michela Giusti a écrit :
> Dear list,
>
>   I did an ENFA analysis and then I used MADIFA to produce an habitat
> suitability map.
>
> I attached the legends results as jpg (sorry for low resolution).
>
> Can you help me in explaining the unit of mesaure obtained from the
> analysis? percentage of what? and distance (m, Km,...)?
>
>   Any help would be appreciated....
>
> Thank you very much.
>
> michela
>
>
>
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Mathieu Basille, PhD

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University of Florida \\
Fort Lauderdale Research and Education Center
(+1) 954-577-6314
http://ase-research.org/basille

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