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 _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
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