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MissForest Imputation

impute_miss_forest.Rd

A wrapper around the missForest::missForest(). Impute missing values using recursive running of random forests until convergence. This is a non-parametric method and works for both MAR and MNAR missing data.

Usage

impute_miss_forest(x, by = NULL, seed = 123, ...)

# S3 method for class 'glyexp_experiment'
impute_miss_forest(x, by = NULL, seed = 123, ...)

# S3 method for class 'matrix'
impute_miss_forest(x, by = NULL, seed = 123, ...)

# Default S3 method
impute_miss_forest(x, by = NULL, seed = 123, ...)

Arguments

x

Either a glyexp_experiment object or a matrix. If a matrix, rows should be variables and columns should be samples.

by

Either a column name in sample_info (string) or a factor/vector specifying group assignments for each sample. Used for grouping when imputing missing values.

seed

Integer seed for random number generation. Default is 123.

...

Additional arguments to pass to missForest::missForest().

Value

Returns the same type as the input. If x is a glyexp_experiment, returns a glyexp_experiment with missing values imputed. If x is a matrix, returns a matrix with missing values imputed.