spfilteR 2.2.0
- 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 2.1.0
- 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 2.0.0
- 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
spfilteR 1.1.5
- fix minor bug in help pages
spfilteR 1.1.4
- update citation information
- fix: use isTRUE(all.equal()) instead of “==” on numeric vectors
spfilteR 1.1.3
spfilteR 1.1.2
- fix broken links
- update citation information
spfilteR 1.1.1
- 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 1.1.0
- 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 1.0.0
- include
MI.decomp() to decompose Moran’s I
- rename
MI.resid()
- prepare for CRAN submission
spfilteR 0.2.0
lmFilter() and glmFilter() now also
support unsupervised eigenvector selection based on the significance of
residual autocorrelation
spfilteR 0.1.0