impute_na  R Documentation 
Impute missing values in a LipidomicsExperiment
impute_na(
data,
measure = "Area",
method = c("knn", "svd", "mle", "QRILC", "minDet", "minProb", "zero"),
...
)
data 
LipidomicsExperiment object. 
measure 
Which measure to use as intensity, usually Area,
Area Normalized or Height. Default is 
method 
The imputation method to use. All methods are wrappers for

... 
Other arguments passed to the imputation method. 
LipidomicsExperiment object with missing values imputed.
data(data_normalized)
# Replace with values calculated using Knearest neighbors
impute_na(data_normalized, "Area", "knn", 10)
# Replace with values calculated from the first K principal components
impute_na(data_normalized, "Area", "svd", 3)
# Replace with Maximum likelihood estimates
impute_na(data_normalized, "Area", "mle")
# Replace with randomly drawn values from a truncated distribution
impute_na(data_normalized, "Area", "QRILC")
# Replace with a minimal value
impute_na(data_normalized, "Area", "minDet")
# Replace with randomly drawn values from a Gaussian distribution
# cerntered around a minimal value
impute_na(data_normalized, "Area", "minProb")
# Replace with zero (not recommended)
impute_na(data_normalized, "Area", "zero")
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