AI-GEOSTATS: Unbiased variances and autocorrelation
I have a spatial data set with fire severities (ordinal response). I
include different predictor variables such as topography, vegetation
cover etc. to predict fire severity using ordinal logistic regression.
To correct the biased variances due to the high autocorrelation, I
applied a robust covariance estimator (function robcov in the Design
package in R). This covariance estimator takes into account
intra-cluster correlation, i.e. autocorrelation within each patch of
This means that I have correctly estimated regression coefficients that
I can use for prediction, and the variances are corrected that allow
valid inference. However, is there still a model missspecification
since the problem with the autocorrelation of the residuals remains?
How shall I deal with this issue?
Thanks for your help!
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