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AI-GEOSTATS: Unbiased variances and autocorrelation

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  • Christof Bigler
    Hi I have a spatial data set with fire severities (ordinal response). I include different predictor variables such as topography, vegetation cover etc. to
    Message 1 of 1 , Mar 8, 2004
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      Hi

      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
      fire severity.
      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!
      Christof


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