specmine (version 3.1.6)

missingvalues_imputation: Missing values imputation

Description

Treats the missing values of a dataset according to a specific method.

Usage

missingvalues_imputation(dataset, method = "value", 
value = 5e-04, k = 5)

Arguments

dataset

list representing the dataset from a metabolomics experiment.

method

imputation method. It can be:

• "value" - replaces the missing values with a specific value

• "mean" - replaces the missing values with the mean of the variables' values

• "median" - replaces the missing values with the median of the variables' values

• "knn" - replaces the missing values with k nearest neighbor averaging

• "linapprox" - replaces the missing values with linear approximation

value

the value to replace the missing values if the method is "value".

k

the number of neighbors if the method is "knn".

Value

Returns the dataset with no missing values.

Examples

# NOT RUN {
  ## Example of impute missing values
  library(specmine.datasets)
  data(propolis)
  dataset = missingvalues_imputation(propolis, method = "value", 
	    value = 0.0005)
# }