NEWS

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spfilteR 2.2.0 (2026-01-08)

• new selection criteria for unsupervised eigenvector selection via stepwise regression:
  • selection based on the corrected Akaike information criterion ('AICc') now available in glmFilter()
  • lmFilter() now supports eigenvector selection based on AIC, AICc, and BIC
• lasso-based eigenvector selection now supported in lmFilter()
• lmFilter() now allows to compute conditional standard errors for regression coefficients using a partial regression framework.
• minor adjustment to the summary method
• add deviance residuals for negative binomial regression models
• add warning message that deviance residuals will become the default in glmFilter() in future releases
• update vignette & tests

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spfilteR 2.1.0 (2025-02-21)

• update vignette to include an example of the negative binomial model
• imrprovement in the console output of function vp()
• improvements and bug fixes in MI.vec() and MI.decomp():
  • correctly handle missing values in each variable separately if multiple variables are supplied
  • check for variable names only inside the function and not in the global environment
  • removal of constant terms supplied to the functions
• improve the handling of missingness in MI.resid()
• minor adjustments to helper functions
• update tests

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spfilteR 2.0.0 (2025-01-22)

• allow for unsupervised eigenvector selection in negative binomial models
  • glmFilter() now supports 'nb' (for negative binomial) as model type
  • adjustments in summary method and helper functions to handle negative binomial models
  • update tests for negative binomial model
• glmFilter() also provides McFadden's adjusted pseudo R-squared for the filtered vs. the unfiltered model
• bug fixes
  • bug fix in help pages of MI.local() and MI.vec() functions
  • resolves an error in lmFilter() and glmFilter() occurring when covariates are supplied as data.frame
• assign variable names to output (if provided)
• improve the handling of missingness in MI.vec(), MI.decomp(), and MI.local()
• update tests

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spfilteR 1.1.5 (2022-08-22)

• fix minor bug in help pages

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spfilteR 1.1.4 (2022-03-09)

• update citation information
• fix: use isTRUE(all.equal()) instead of "==" on numeric vectors

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spfilteR 1.1.3

• update tests

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spfilteR 1.1.2 (2022-01-18)

• fix broken links
• update citation information

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spfilteR 1.1.1 (2021-10-05)

• CRAN resubmission
• improve readability of code
• update author mail address
• include citation

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spfilteR 1.1.0.9000

• improve readability of code
• update author mail address
• include citation

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spfilteR 1.1.0 (2021-05-12)

• CRAN resubmission
• fix minor bug when checking 'tol' in lmFilter() function
• new vignette name
• add new functions
  • MI.local() function to calculate local Moran's I
  • vp() function for variation partitioning
• update reference to MI.local() in documentation files

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spfilteR 1.0.0.9000

• fix minor bug when checking 'tol' in lmFilter() function
• new vignette name
• add new functions
  • MI.local() function to calculate local Moran's I
  • vp() function for variation partitioning
• update reference to MI.local() in documentation files

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spfilteR 1.0.0 (2020-12-07)

• include MI.decomp() to decompose Moran's I
• rename MI.resid()
• prepare for CRAN submission

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spfilteR 0.2.0

• lmFilter() and glmFilter() now also support unsupervised eigenvector selection based on the significance of residual autocorrelation

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spfilteR 0.1.0