[R-sig-Geo] Autologistic regression in R

[Ege Rubak]

OK. At least that helps people understand the basic properties of the data.
The sampling design could also be important for the choice of method. 
You should probably make this part a bit more clear and answer questions 
like:
- Did you make a sparse random sample of locations in a big area?
- Or did you sample a predefined small area extensively?
- Etc...
I can't really offer any specific help, but I would advise you to add a 
bit more detail in case it rings a bell for a helpful soul out there.
/Ege

On 11/15/2017 04:44 PM, Mingke Li wrote:
> Hi Ege,
> 
> 
> Thanks for replying. Sorry for not clearfying the data.
> 
> 
> The raw response data is the actural population counted at the specific 
> sample points. Because my study object is spruce budworm which would 
> cause forest defoliation, what we are interested in are those sample 
> points where spruce budworm population is greater than 7 per brunch. 
> Some of the sample points have zero population, and some have population 
> fewer than 7 per brunch, but these samples don't attract us because 
> spruce budworm are always there; fewer than 7 per brunch is not a 
> problem for forests.
> 
> 
> So what I understand is to set 7 as a threshold to transform the raw 
> response data to 0 (population<7) and 1(population>=7). Also some papers 
> point out the significance of encountering the spatial autocorrelation 
> when dealing these species distribution problem, that is why I come 
> across the autologistic regression.
> 
> 
> This approach is so new to me, so I may have some misunderstanding. 
> Thanks again.
> 
> 
> Erin
> 
> ------------------------------------------------------------------------
> *From:* R-sig-Geo <r-sig-geo-bounces at r-project.org> on behalf of Ege 
> Rubak <rubak at math.aau.dk>
> *Sent:* November 15, 2017 10:59:05 AM
> *To:* r-sig-geo at r-project.org
> *Subject:* Re: [R-sig-Geo] Autologistic regression in R
> 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
>> 
>> 
>>        [[alternative HTML version deleted]]
>> 
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>
> 
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo