VIM-package	VIM-package
(at	kNN
)`	kNN
.apply_weight_fun	dot-apply_weight_fun
.robust_scale	dot-robust_scale
.weighted_qr_solve	dot-weighted_qr_solve
2	kNN
=	kNN
aggr	aggr
alphablend	alphablend
Animals_na	Animals_na
are	kNN
as.mids.vimmi	vim_as_mids
barMiss	barMiss
bcancer	bcancer
bgmap	bgmap
bootstrap_resample	bootstrap_resample
brittleness	brittleness
bubbleMiss	growdotMiss
build_gam_formula	build_gam_formula
by	kNN
cellIRWLS	cellIRWLS
cellWeights	cellWeights
cellWeightsFromResiduals	cellWeightsFromResiduals
cellWeightsMCD	cellWeightsMCD
check`);	kNN
chorizonDL	chorizonDL
CMD	kNN
colic	colic
collisions	collisions
colormapMiss	colormapMiss
colormapMissLegend	colormapMiss
colSequence	colSequence
colSequenceHCL	colSequence
colSequenceRGB	colSequence
complete.vimmi	vim_complete
complete_model_info	complete_model_info
computed	kNN
countInf	countInf
countNA	countInf
diabetes	diabetes
Distances	kNN
during	kNN
evaluation	evaluation
extract_model_info	extract_model_info
food	food
gapMiss	gapMiss
governed	kNN
gowerD	gowerD
growdotMiss	growdotMiss
histMiss	histMiss
hotdeck	hotdeck
huber_weight	huber_weight
iimagMiss	matrixplot
impPCA	impPCA
imputeCellEM	imputeCellEM
imputeCellIRMI	imputeCellIRMI
imputeCellM	imputeCellM
imputeCellMCD	imputeCellMCD
imputeCellMM	imputeCellMM
imputeCellReg	imputeCellReg
imputeCellwise	imputeCellwise
imputeRobust	imputeRobust
imputeRobustChain	imputeRobustChain
initialise	initialise
inject_uncertainty	inject_uncertainty
irmi	irmi
kNN	kNN
kola.background	kola.background
lse_synthetic	lse_synthetic
lse_synthetic_rules	lse_synthetic_rules
makeMissing	makeMissing
mapMiss	mapMiss
marginmatrix	marginmatrix
marginplot	marginplot
matchImpute	matchImpute
matrixplot	matrixplot
maxCat	maxCat
medianSamp	medianSamp
midastouch_donors	midastouch_donors
mosaicMiss	mosaicMiss
most	kNN
msecor	evaluation
msecov	evaluation
new_vimmi	new_vimmi
nrmse	evaluation
oob_predictions	oob_predictions
OpenMP	kNN
overimpute	overimpute
pairsVIM	pairsVIM
parcoordMiss	parcoordMiss
pbox	pbox
pfc	evaluation
plot.aggr	aggr
plot.vimmi	plot.vimmi
plot.vimpute_overimpute	overimpute
pmm_donor_selection	pmm_donor_selection
pmm_observed_scores	pmm_observed_scores
prepare	prepare
print.aggr	aggr
print.summary.aggr	aggr
print.vimmi	vimmi
print.vimpute_overimpute	overimpute
print.vimpute_spec	vimpute_spec
pulplignin	pulplignin
rangerImpute	rangerImpute
register_gam_learners	register_gam_learners
register_vimpute_method	register_vimpute_method
regressionImp	regressionImp
rugNA	rugNA
sampleCat	sampleCat
SBS5242	SBS5242
scattJitt	scattJitt
scattmatrixMiss	scattmatrixMiss
scattMiss	scattMiss
see	kNN
sleep	sleep
spineMiss	spineMiss
summary.aggr	aggr
summary.vimmi	vimmi
tableMiss	tableMiss
tao	tao
testdata	testdata
there.	kNN
threads	kNN
TKRmatrixplot	matrixplot
toydataMiss	toydataMiss
tukey_weight	tukey_weight
unregister_vimpute_method	unregister_vimpute_method
unwrap_raw_model	unwrap_raw_model
VIM	VIM-package
vimmi	vimmi
vimpute	vimpute
vimpute_methods	vimpute_methods
vimpute_search_space	vimpute_search_space
vimpute_spec	vimpute_spec
vimpute_tune_control	vimpute_tune_control
vim_as_mids	vim_as_mids
vim_complete	vim_complete
vs_gam	vimpute_spec
vs_ranger	vimpute_spec
vs_regularized	vimpute_spec
vs_robgam	vimpute_spec
vs_robust	vimpute_spec
vs_xgboost	vimpute_spec
whose	kNN
wine	wine
with.vimmi	with.vimmi
xgboostImpute	xgboostImpute
[gowerD()],	kNN
`options(VIM.ncores	kNN
`R	kNN
