[R-sig-Geo] Appropriate variogram model

[Ankur Sarker]

Dear Dr. Benedikt Gräler,
Thank you for your advice. Now, I have found some directs to move on. 
Actually, I do not have enough background to analyze by myself. Based on your suggestions, I have plotted the variogram. I think there are daily and weekly seasonality.
According to your suggestions, I am trying to model daily seasonality. It would be great if you can give me more advice.
With Best Regards,Ankur 

    On Wednesday, May 17, 2017 6:10 AM, Dr. Benedikt Gräler <b.graeler at 52north.org> wrote:
 

 Dear Ankur,

I see two issues from your plot:
i) there seems to be a seasonality in your data (maybe daily?) as the 
sample variogram grows up to half the length of your temporal axis and 
then drops again
ii) the starting values of your fitting routine are far off from what 
can be deduced from the sample variogram. Hence, the numerical routines 
have a hard time to identify the correct values. Additionally, the 
parameters are of different orders of magnitude further complicating the 
numerical fit. Manual re-scaling might help.

Try adding the parameter "scales=list(arrows=F)" for a visual assessment 
of the empirical variogram; in your case

plot(var, wireframe=T, scales=list(arrows=F))

This reveals that the variogram indicates the same strength of 
dependence for values 24 and 0 hours apart -> daily cycle? I'd suggest 
to model the daily cycle first and then to model the spatio-temporal 
variogram of the residuals.

HTH,

  Ben



On 08/05/2017 06:33, Ankur Sarker via R-sig-Geo wrote:
> Hi,
> 
> Can anyone suggest me the most appropriate variogram model to fit my data?
> 
> I have tried three different models and results are too bad. Here is the 
> comparison of different variogram models as attached.
> 
> Thanks,
> Ankur
> 
> 
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-- 
Dr. Benedikt Gräler
52°North Initiative for Geospatial Open Source Software GmbH
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E-Mail: b.graeler at 52north.org
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