I wish to estimate a variogram for spatially distributed price data in Tanzania. I'm new to both spatial statistics and gstat, and have a couple questions.
(1) I can SEE spatial patterns in price, and moran's I is about 0.2, so I know there is spatial correlation. But when I plot my variogram using the code below, semivariance is flat across distance. (Screenshot in dropbox link below, as well as the tzprice1 shapefile for replication.) Why would this be? Perhaps I need to specify smaller intervals, and a smaller range? And if so, how?
tzprice1_v <- tzprice1[!is.na(tzprice1@data$prodp), ] pr.v <- variogram(prodp ~1, tzprice1_v) plot(pr.v)
(2) I am unable to estimate the variogram using fit.variogram, and I'm guessing that this is because the underlying data don't show the right shape. Is this correct? But just in case, I'm using the code below... is it correct to simply guess the sill, nugget, and range starting values in this way, from the plot that I did above?
Shapefile and screenshot here: https://www.dropbox.com/sh/oad1xfcpcugkulh/AACec_FuUZqCHR9-Jicohgm9a?dl=0