Hi Erin,
It is not quite clear to me what your data is. From your text I
understand that you have a number of locations where you have measured
the population of a specific insect (count variable?) together with
independent/explanatory variables at these same locations. Is the
"population" sometimes zero? Is it even restricted to be binary (0/1),
which I guess would be required for logistic regression to make sense?
Cheers,
Ege
On 11/15/2017 02:46 AM, Mingke Li wrote:
Hi,
I am new to autologistic regression and R. I do have questions when starting a
project in which I believe autologistic regression (spdep package) is needed.
I have a point layer whose attribute table stores the values of the dependent
variable (population of a kind of insect), all the independent variables
(environmental factors), and the associated latitude and longitude. I hope to
to fit an autologistic model to analyze which factors or combinations of
factors have effects on the presence/absence of the insect (1 or 0).
I found other papers which applied autologistic regression in their study
almost used a grid system and defined their window sizes. So, my question is do
I have to convert my point layer into a grid system if I want to do this
analysis with R?
Also, what should I consider when I generate the grid system? How to determine
a proper cell size? How about the searching window (neighbourhood) size?
Many Thanks.
Erin
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