detect.MCAR.MNAR.MAR: detect.MCAR.MNAR.MAR from juuussi/impute-metabo

In BeanLabASU/metabimpute: Missingness Evaluation, Simulation and Imputation in Metabolomics

detect.MCAR.MNAR.MAR from juuussi/impute-metabo

Usage

detect.MCAR.MNAR.MAR(
  data,
  MissingVar,
  MAR_MNAR,
  alpha = 0.05,
  percentage = 0.6,
  gof_Method = "kolmogorov"
)

Arguments

data	, data matrix
MissingVar	vector containing the columns numbers of the data matrix with missing values that are less than 80 \item MAR_MNARvector containing the columns with missing values that have MAR or MNAR missigness (use the detect.miss.MNAR.MAR function) \item alpha, Significance level , default is 0.05 \item percentage \item gof_Methodmethod of goodness of fit testing, 'kolmogorov' or 'cucconi'

results list of vectors : MCAR = vector conatining the column numbers of MCAR variables, MNAR = vector conatining the column numbers of MNAR variables , MAR = vector conatining the column numbers of MAR variables , Excluded_marmnar = vector conatining the column numbers of excluded MAR or MNAR variables that have more than 60 ExcludedVar = vector conatining the column numbers of excluded variables that have more than 80 CompleteVar = conatining the column numbers of variables without missing values. detect.MCAR.MNAR.MAR from juuussi/impute-metabo

BeanLabASU/metabimpute documentation built on Feb. 5, 2023, 11:41 p.m.