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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.

spmodel 0.3.0

CRAN release: 2023-03-10

Minor updates

  • Added the varcomp function to compare variance components.
  • Added an error message when there are NA values in predictors.
  • Added an error message when the design (model) matrix is not invertible (i.e., perfect collinearities are detected).
  • Added support for plotting anisotropic level curves of equal correlation when the which argument to plot() contains 8.
  • Renamed residuals() type raw to response to match stats::lm().
  • Changed class of splm() output to "splm" from "spmod" or "splm_list" from "spmod_list".
  • Changed class of spautor() output to "spautor" from "spmod" or "spautor_list" from "spautor_list".
  • Changed class of splmRF() output to "splmRF" from "spmodRF" or "splmRF_list" from "spmodRF_list".
  • Changed class of spautorRF() output to "spautorRF" from "spmodRF" or "spautorRF_list" from "spmodRF_list".
  • Methods corresponding to a generic function defined outside of spmodel are now all documented using an .spmodel suffix, making it easier to find documentation of a particular spmodel method for the generic function of interest.
  • Added an error when random effect grouping variables or partition factors are numeric.
  • Added an error when random effect or partition factor levels in newdata are not also in data.
  • Updated citation information.

Bug fixes

  • Fixed a bug that produced irregular spacing in an error message for spcov_initial().
  • Fixed a bug that prevented proper display of row names when calling predict() with interval = "confidence".
  • Fixed a bug that sometimes caused miscalculations in model-fitting and prediction when random effect or partition factor variables were improperly coerced to a different type.
  • Fixed bugs that sometimes caused miscalculations in certain model diagnostics.
  • Fixed inconsistencies in several non-exported generic functions.
  • Fixed a bug that prevented names from appearing with output from certain model diagnostics.

spmodel 0.2.0

CRAN release: 2022-11-11

  • spmodel v0.3.0 changed the names of spmod, spmodRF, spmod_list, and spmodRF_list objects.

Minor updates

  • splm() and spautor() allow multiple models to be fit when the spcov_type argument is a vector of length greater than one or the spcov_initial argument is a list (with length greater than one) of spcov_initial objects.
    • The resulting object is a list with class spmod_list. Each element of the list holds a different model fit.
    • glances() is used on an spmod_list object to glance at each model fit.
    • predict() is used on an spmod_list object to predict at the locations in newdata for each model fit.
  • Added the splmRF() and spautorRF() functions to fit random forest spatial residual models.
    • The resulting object has class spmodRF (one spatial covariance) or spmodRF_list (multiple spatial covariances)
    • These objects are built for use with predict() to perform prediction.
  • Added the covmatrix() function to extract covariance matrices from an spmod object fit using splm() or spautor().
  • Minor vignette updates.
  • Minor documentation updates.

Bug fixes

  • Fixed a bug that prevents display of spatial covariance type in summary of spmod objects.
  • Fixed a bug that prevented prediction of factor variables when all levels of all factor variables did not appear in newdata.

spmodel 0.1.1

CRAN release: 2022-10-20

Minor updates

  • Updated unit tests so that they are compatible with an upcoming version of Matrix.

spmodel 0.1.0

CRAN release: 2022-08-12

This is the initial release of spmodel.