NEWS
VIM 6.2.3
- default robust regression method for irmi for numeric variables changes from rlm to lmrob.
VIM 6.1.1 (2021-07-22)
- ordFun as parameter of kNN to control the function applied to ordinal variables
- methodStand option in gowerD and kNN to switch between range and interquartile range for the standardization of numerical variables
- donorcond in kNN and hotdeck extended so it also accepts NULL as list element and multiple conditions as character vector
VIM 6.0.2
- error message in
hotdeck()
when ord_var and variable overlap
- family argument of class 'family' now work in regressionImp
VIM 6.0.1
- add new vignettes explaining all remaining imputation methods (
irmi()
,
kNN()
, hotdeck()
and regressionImp()
). Thanks @wolfgangrannetbauer
(#44, #45)
- Allow missing and imputed values in several visualization functions.
- Add
tableMiss()
: A table that highlights missing and imputed values via
colors (#47).
- Bug fix for kNN (#48) Thanks @torockel
VIM 6.0.0 (2020-05-08)
- extend documentation with new vignettes and pkgdown
- add rangerImpute() to impute values with
ranger::ranger()
(#35)
- remove support for survey objects (#36)
- remove exports for VIMGUI (#40)
- change data.table dependency from depends to imports (#41)
- bugfixes for
irmi()
with logical and integer columns (#42)
VIM 5.1.1 (2020-03-10)
- updates for
gowerD()
- separate help pages for
maxCat()
and sampleCat()
- remove links to certain packages
VIM 5.0.0
New datasets
- bcancer
- brittleness
- colic
- diabetes
- food
- pulplignin
- toydataMiss
- wine
VIM 4.9.1
VIM 4.8.0 (2019-02-11)
- fixed a bug in the distance computation when different variable types are used
VIM 4.7.18
- added
imp_var
and imp_suffix
to irmi()
, so it is more consistent with the other functions (#27)
VIM 4.7.17
- added parameter addRF, only RF to
kNN()
, to use random forest in combination with kNN()
VIM 4.7.12
- testthat package used for all tests
- added travis automatically building/checking
- covr for code coverage (vis functions are currently not covered by any tests)
VIM 4.7.1
- new imputation function
matchImpute()
for imputing randomly within groups
VIM 4.7.0 (2017-04-11)
- remove handling of
impNA
in hotdeck()
- add regression tests
- bugfix for
irmi()
with factors (#13). Thanks @Deleetdk
- bugfix with colorspace package (#4)
VIM 4.6.1
- use ordered logistic regression for ordinal variables in
irmi()
(#23)
- add support for ordered factors (#7)
- bugfixes (#8, #9)
VIM 4.6.0 (2016-10-17)
- bugfixes for
kNN()
and data.table
- bugfix for labelled vars in
hotdeck()
- add JSS citation
- bugfix, if a
data.frame
is passed to irmi()
(#6)
VIM 4.5.0 (2016-06-29)
- new option for
kNN()
: weightDist
to use the distances for the k nearest neighbours as weights
- The R function
which.minN()
is not used anymore, instead there is a C++ function, kNN()
is now about 1.6 times faster on a replication (100x) of the sleep dataset
- Bytecompile is enabled
VIM 4.4.0
- bugfix wrong observations marked as imputed in
hotdeck()
- random sorting is now used in
hotdeck()
if no ord_var
is defined
VIM 4.3.0 (2015-07-07)
- bugfix for
hotdeck()
with makeNA
VIM 4.2.3
- bugfix for the computation of distances for ordered variables
VIM 4.2.1
- new option for
kNN()
useImputedDist
if the imputed values of a variable should be used in subsequent imputation of another variable.
VIM 4.2.0
- bug fixed in
irmi()
with newer version of nnet (multinom) and if residual scale can not be computed (noise)
- Improvement Gower dist with only missing values in data.x or data.y
VIM 4.1.0 (2014-10-25)
- new parameter
modelFormula
in irmi()
- bug fixes in
irmi()
- updated
hotdeck()
based on data.table -> faster and quite stable
- bug fix if range of a variable is 0 in gower.dist
- small fixed
kNN()
VIM 4.0.1
- small bugfix for using
makeNA
in kNN()
- "Nothing to impute"-Error is now a warning
imp_var
now updates existing TF imp_vars
(with warning)
VIM 4.0.0 (2013-10-10)
- new pacakge VIMGUI contains all GUI functions
- vignettes moved to VIMGUI
- new imputation function
regressionImp()
- roxygen style comments -> help files