Changelog

Source: NEWS.md

spfilteR 2.2.02026-01-08

  • 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

spfilteR 2.1.02025-02-21

  • 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

spfilteR 2.0.02025-01-22

  • 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
  • assign variable names to output (if provided)
  • improve the handling of missingness in MI.vec(), MI.decomp(), and MI.local()
  • update tests

spfilteR 1.1.52022-08-22

  • fix minor bug in help pages

spfilteR 1.1.42022-03-09

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

spfilteR 1.1.3

  • update tests

spfilteR 1.1.22022-01-18

  • fix broken links
  • update citation information

spfilteR 1.1.12021-10-05

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

spfilteR 1.1.0.9000

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

spfilteR 1.1.02021-05-12

  • 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

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

spfilteR 1.0.02020-12-07

spfilteR 0.2.0

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

spfilteR 0.1.0