spmodel 0.5.0
CRAN release: 2023-10-25
Minor updates
- Predictions can now be made for prediction locations whose random effect levels are not present in the observed data
- When this occurs, the random-effect covariance between the observed data and these prediction locations is assumed to be zero.
- The default for
local = TRUEinsplm()andspglm()now uses thekmeansassignment method with group sizes approximately equal to 100.- Previously, the
randomassignment method was used with group sizes approximately equal to 50.
- Previously, the
- The default for
local = TRUEinpredict()andaugment()now uses 100 local neighbors.- Previously, 50 local neighbors were used.
- Moved the “A Detailed Guide to
spmodel” and “Technical Details” vignettes to the package website. - Added a “Spatial Generalized Linear Models in
spmodel” vignette to the package website. - Changed name of “An Overview of Basic Features in
spmodel” vignette to “An Introduction tospmodel” and changed output type from PDF to HTML. - Other minor vignette updates.
- Minor documentation updates.
Bug fixes
- Fixed a bug that occurred with prediction for success/failure binomial data (e.g., Bernoulli data) when
localinpredict()wasTRUE. - Fixed a bug that could affect simulating data using
sprbinom()when thesizeargument was different from1. - Fixed a bug that could cause local prediction to fail when only one level of a random effect was present in the prediction site’s local neighborhood.
- Fixed a bug that could cause an error when local estimation was used for the
"sv-wls"estimation method. - Fixed a bug that caused undesirable behavior from
tidy()whenconf.levelwas less than zero or greater than one.
spmodel 0.4.0
CRAN release: 2023-05-26
Major updates
- Added an
spglm()function to fit spatial generalized linear models for point-referenced data (i.e., generalized geostatistical models). - Added an
spgautor()function to fit spatial generalized linear models for areal data (i.e., spatial generalized autoregressive models).-
spgautor()syntax is very similar tospautor()syntax. - Poisson, negative binomial, binomial, beta, gamma, and inverse Gaussian families are accommodated.
-
spgautor()fitted model objects use the same generics asspautor()fitted model objects.
-
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 coerceMif given as a matrix (instead of a vector). - Fixed a bug in
esv()that prevented coercion ofPOLYGONgeometries toPOINTgeometries ifdatawas ansfobject. - Fixed a bug in
esv()that did not removeNAvalues from the response. - Fixed a bug in
splm()andspautor()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 whenspcov_typewas"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 thelocalmethod 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
varcompfunction to compare variance components. - Added an error message when there are
NAvalues 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
whichargument toplot()contains8. - Renamed
residuals()typerawtoresponseto matchstats::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
spmodelare now all documented using an.spmodelsuffix, making it easier to find documentation of a particularspmodelmethod 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
newdataare not also indata. - 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()withinterval = "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
-
spmodelv0.3.0 changed the names ofspmod,spmodRF,spmod_list, andspmodRF_listobjects.
Minor updates
-
splm()andspautor()allow multiple models to be fit when thespcov_typeargument is a vector of length greater than one or thespcov_initialargument is a list (with length greater than one) ofspcov_initialobjects. - Added the
splmRF()andspautorRF()functions to fit random forest spatial residual models.- The resulting object has class
spmodRF(one spatial covariance) orspmodRF_list(multiple spatial covariances) - These objects are built for use with
predict()to perform prediction.
- The resulting object has class
- Added the
covmatrix()function to extract covariance matrices from anspmodobject fit usingsplm()orspautor(). - Minor vignette updates.
- Minor documentation updates.