spmodel v0.4.0

spmodel 0.4.0

Major updates

• Added an spglm() function to fit spatial generalized linear models for point-referenced data (i.e., generalized geostatistical models).
  • spglm() syntax is very similar to splm() syntax.
  • Poisson, negative binomial, binomial, beta, gamma, and inverse Gaussian families are accommodated.
  • spglm() fitted model objects use the same generics as splm() fitted model objects.
• Added an spgautor() function to fit spatial generalized linear models for areal data (i.e., spatial generalized autoregressive models).
  • spgautor() syntax is very similar to spautor() syntax.
  • Poisson, negative binomial, binomial, beta, gamma, and inverse Gaussian families are accommodated.
  • spgautor() fitted model objects use the same generics as spautor() fitted model objects.

Minor updates

• In augment(), made the level and local arguments explicit (rather than being passed to predict() via ...).
• Added offset support for relevant modeling functions.
• Minor documentation updates.
• Minor vignette updates.

Bug fixes

• Fixed a bug in spcov_params() that yielded output with improper names when a named vector was used as an argument.
• Fixed a bug in spautor() that did not properly coerce M if given as a matrix (instead of a vector).
• Fixed a bug in esv() that prevented coercion of POLYGONgeometries to POINT geometries if data was an sf object.
• Fixed a bug in esv() that did not remove NA values from the response.
• Fixed a bug in splm() and spautor() that caused an error when random effects or partition factors were ordered factors.
• Fixed a bug in spautor() that prevented an error from occurring when a partition factor was not categorical or not a factor
• Fixed a bug in covmatrix(object, newdata) that returned a matrix with improper dimensions when spcov_type was "none".
• Fixed a bug in predict() that caused an error when at least one level of a fixed effect factor was not observed within a local neighborhood (when the local method was "covariance" or "distance").
• Fixed a bug in cooks.distance() that used the Pearson residuals instead of the standarized residuals.