Changes in version 0.4.0 (2025-10-21) Major Updates - Added a vignette to the SSN2 website titled "Adding Explanatory Variables to 'SSN' Objects Directly in R Using StreamCat". - Added a vignette to the SSN2 website titled "Fitting 'SSN' Models to Large Data Sets and Making Predictions (i.e., Kriging)" Minor Updates - Changed the default size argument to the local argument in ssn_lm() and ssn_glm() from 100 to 200. This enhances the approximation's accuracy but can slightly increase computational complexity. - Changed the default size argument to the local argument in predict() and augment() from 2000 to 4000. This enhances the approximation's accuracy but can slightly increase computational complexity. Bug Fixes - Fixed a bug that could improperly order observations when local was specified (for large data sets) in ssn_lm() or ssn_glm(). - Fixed a bug that could improperly order local_index in ssn_lm() or ssn_glm() model objects. Changes in version 0.3.1 (2025-09-30) Bug fixes - Added a dependency on spmodel version at least 0.7.0 so that AUROC() methods are properly called. - Fixed a bug introduced in version 0.3.0 that prevented partition_factor from working properly when non-NULL (#32). Changes in version 0.3.0 (2025-08-18) Major Updates - Added support for the emmeans R package for estimating marginal means of ssn_lm() and ssn_glm() models. - Added support for applications to large data sets. The ssn_create_bigdist() function was added to create large distance matrices using the filematrix R package. Estimation for large data sets is performed by leveraging the local argument to ssn_lm() and ssn_glm(). Prediction for large data sets is performed by leveraging the local argument to predict() (and augment()). When local is used, SSN2 looks for distance matrices created using ssn_create_bigdist(). - Added support for Gaussian tail-up and tail-down covariance functions. Minor Updates - Updated ssn_import() so that it does not force an overwrite of the netgeom column when it already exists. - Add a verbose argument to ssn_import(), ssn_import_predpts(), and createBinaryID() to control whether warning messages are printed to the R console. - Added the na.action argument to predict.ssn_lm() and predict.ssn_glm() functions to clarify that missing values in newdata return an error. - Changed the type argument in augment() for ssn_glm() models to type.predict to match broom::augment.glm(). - augment() for ssn_glm() models now returns fitted values on the link scale by default to match broom::augment.glm(). - Added a type.residuals argument for ssn_glm() models to match broom::augment.glm(). - Updated logLik() to match lm() and glm() behavior. logLik() now returns a vector with class logLik and attributes nobs and df. - Added support for using AIC() and BIC() from stats and removed SSN2-specific AIC() methods. - Added a warning argument to glances() that determines whether relevant warnings should be displayed or not. - Added a warning message to glances() about interpreting likelihood-based statistics (e.g., AIC, AICc, BIC) when a one model has estmethod = "ml" and another model has estmethod = "reml". - Added a warning message to glances() about interpreting likelihood-based statistics (e.g., AIC, AICc, BIC) when two models with estmethod = "reml" have distinct formula arguments. - Added a warning message to glances() about interpreting likelihood-based statistics (e.g., AIC, AICc, BIC) when two models have different sample sizes. - Added a warning message to glances() about interpreting likelihood-based statistics (e.g., AIC, AICc, BIC) when two models have different family supports (which can happen with ssn_glm() models). - Added a cloud argument to Torgegram() to return a cloud Torgegram. - Added the ability to pass custom cex to plot.Torgegram(). - Added a robust semivariogram option to Torgegram(); see the robustargument to Torgegram() - Added an AUROC() function to compute the area under the receiver operating characteristic (AUROC) curve for ssn_glm models when family is "binomial" and the response is binary (i.e., represents a single success or failure). - Added a type argument to loocv() when cv_predict = TRUE and using ssn_glm() models so that predictions may be obtained on the link or response scale. - Added support for "terms" prediction for ssn_lm() and ssn_glm() models. - Added scale and df arguments to predict() for ssn_lm() models. - Add dispersion argument to predict() for ssn_glm() models. - Minor documentation updates. - Minor code maintenance updates. Bug Fixes - Fixed a bug that caused incorrect degrees of freedom for the likelihood ratio test (anova(model1, model2)) when estmethod is "ml" for both models #25. - Fixed a bug that caused an error in anova(object1, object2) when the name of object1 had special characters (e.g., $). Changes in version 0.2.1 (2024-08-28) Minor Updates - Enhanced numeric stability of deviance and pseudo R-squared for ssn_glm() models when family = "beta" (#23). - Updated reexport.Rd to reflect changes in spmodel v0.8.0's handling of AIC() and AICc(). Changes in version 0.2.0 (2024-07-26) Major Updates - Significant testing, documentation, and auxiliary (e.g., README.md) updates as part of a submission to Journal of Open Source Software. Relevant issues associated with the review are available at #11, #12, #13, #14, #15, #16, #17, #20, #21. The review is linked here. - Added support for geopackage file formats in the .ssn folder that is accessed when importing SSN objects via ssn_import(). Minor Updates - Added ssn_names() to return column names in the edges, obs, and preds elements of an SSN object. - Changed Matrix::rankMatrix(X, method = "tolNorm2") to Matrix::rankMatrix(X, method = "qr") to enhance stability when determining linear independence in X, the design matrix of explanatory variables. - Replaced an error message with a warning message when X has perfect collinearities (i.e., is not full rank). - Removed format_additive argument from ssn_import() because of transition to geopackage support, which eliminates the need to convert additive function values to text. - Added the create_netgeom() function to create the network geometry column for the edges, obs, and preds elements in an SSN object. - Minor vignette updates. - Minor documentation updates. Bug Fixes - Fixed a bug in SSN_to_SSN2() that caused an error using ssn_write() with no prediction sites. - Replaced names.SSN() with ssn_names(), as names.SSN() prevented proper naming of elements in the SSN object. Changes in version 0.1.1 (2024-01-15) Minor Updates - Changed network geometry name from netgeometry to netgeom to avoid exceeding the 10 character limit for column/field names while writing to shapefiles (#2). - Added an error message when family is missing in ssn_glm() (#8). - Added a deprecation warning for SSN_to_SSN2(). - Minor stability updates. - Minor error message updates. - Minor documentation updates. Bug Fixes - Fixed a bug in Torgegram() that prevented intended computation when cutoff was specified. - Fixed a bug in plot.Torgegram() that occasionally prevented proper spacing of the legend. - Fixed a bug that prevented proper printing of the dispersion parameter from ssn_glm() model objects (and their summaries) when all covariance parameters were known. - Fixed a bug that prevented simulation when euclid_type was "none". - Fixed a bug that could cause improper prediction behavior when taildown_type was "spherical". - Fixed a bug that printed response residuals instead of deviance residuals for ssn_glm() objects. Changes in version 0.1.0 (2023-11-08) - Initial CRAN submission.