Function reference • MissImp

All functions
`ConfusionMatrix()`	Confusion Matrix
`F1_Score_micro()`	F1 Score (micro averaged)
`MIFAMD()`	MIFAMD: modified multiple imputation with FAMD
`MI_EM_amelia()`	MI_EM_amelia: Multiple imputation with EM
`MI_missRanger()`	MI_missRanger
`MissImp()`	MissImp: A package for imputing missing values This package provides missing data generation method with a given mechanism and a given proportion, various single and multiple imputation methods combined with bootstrap or jackknife resampling method, as well as evaluation matrix of the imputation result.
`Mode_cat()`	Mode_cat
`Precision_micro()`	Precision (micro averaged)
`Recall_micro()`	Recall (micro averaged)
`TestMCARNormality()`	TestMCARNormality: Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random
`VA_fact()`	VA_fact
`bootsample()`	bootsample: create several dataframes by bootstrap resampling
`combine_boot()`	combine_boot: combine imputed bootstrap datasets
`combine_jack()`	combine_jack: combine imputed jackknife datasets
`convert()`	Conversion of non-factor/non-numeric variables.
`dict_level()`	dict_level
`dict_onehot()`	dict_onehot
`dummyVars()` `print(<dummyVars>)` `predict(<dummyVars>)` `contr.ltfr()` `class2ind()`	Create A Full Set of Dummy Variables
`dummy_test()`	dummy_test: dummy t-chi-test for MCAR
`dummy_test_matrix()`	dummy_test_matrix: Create the matrix of p-value for dummy t-chi-test
`em()`	em: modified EM Imputation with probability vector
`estim_ncpFAMD()`	estim_ncpFAMD
`factor_encode()`	factor_encode
`factor_ordinal_encode()`	factor_ordinal_encode
`generate_miss()`	generate_miss: Generate missing values with different mechanisms
`generate_miss_ls()`	generate_miss_ls: Generate a list of incomplete dataframes with different missing mechanisms
`imputeFAMD()`	imputeFAMD
`imputeMFA_mod()`	imputeMFA_mod
`imputeUnivariate()`	Univariate Imputation
`impute_mod()`	impute_mod
`jacksample()`	jacksample: create several dataframes by jackknife resampling
`kNN()`	kNN
`ls_F1()`	List of MSE
`ls_MSE()`	List of MSE
`mcar_test_combined()`	MCAR Test
`missForest()`	missForest: modified missForest with onehot probability
`missRanger()`	Fast Imputation of Missing Values by Chained Random Forests
`missRanger_mod_draw()`	missRanger_mod_draw
`monot_quantil()`	monot_quantil
`normalize_num()`	normalize_num
`ordinal_encode()`	ordinal_encode
`pmm()`	Predictive Mean Matching
`prepare_df_for_em()`	prepare_df_for_em
`prob_vector_cat()`	prob_vector_cat
`produce_NA()`	generation of missing values on complete or incomplete data according to different missingness mechanisms and patterns
`result_mice()`	result_mice: Multiple imputation with bayesian method
`revert()`	Revert conversion.
`test_abalone`	Part of Abalone dataset for test
`typeof2()`	A version of `typeof` internally used by `missRanger`.
`which.max.random()`	which.max.random

Reference

All functions