I have a dataset like this:
sites years Var1 Var2
1 1960 505 3.013833
1 1961 533 4.118784
1 1962 609 14.96386
1 1963 465 -3.74409
1 1964 837 41.70164
1 1965 727 29.53478
2 1960 493 3.269235
2 1961 535 5.386015
2 1962 608 16.26244
2 1963 469 -2.09736
2 1964 830 42.01942
2 1965 715 29.92867
3 1960 489 5.630015
3 1961 540 8.694733
3 1962 615 19.60908
3 1963 480 1.666236
3 1964 836 45.12964
3 1965 714 32.36178
4 1960 473 2.752683
4 1961 533 6.521744
4 1962 601 16.89496
4 1963 475 -0.2503
4 1964 817 41.86903
4 1965 686 28.54376
5 1960 476 4.337246
5 1961 540 8.601403
5 1962 610 18.99233
5 1963 479 1.336739
5 1964 822 43.73037
5 1965 692 30.30235
Meantime, I have the spatial location (longitude, latitude) for each site.
Among these sites, spatial autocorrelation exists. Within each site, for the
variables ¡°Var1¡± and ¡°Var2¡±, temporal autocorrelation also exists. I want
to calculate the correlation between Var1 and Var2 using ¡°correlation
coefficient¡±. My question is that how can I add the information of spatial and
temporal autocorrelation into my analysis. I know that, for only spatial
autocorrelation, we can use ¡°modified t-test¡± to do the analysis. But I have
no idea how to do it when considering the spatial and temporal autocorrelation
together?
Any suggestions?
Thanks so much.
---
Jian Zhang
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