clean_data {topolow}R Documentation

Clean Data by Removing MAD-based Outliers

Description

Removes outliers from numeric data using the Median Absolute Deviation method. Outliers are replaced with NA values. This function is particularly useful for cleaning parameter tables where each column may contain outliers.

Usage

clean_data(x, k = 3, take_log = FALSE)

Arguments

x

Numeric vector to clean

k

Numeric threshold for outlier detection (default: 3)

take_log

Logical. Whether to log transform data before outlier detection (default: FALSE)

Value

A numeric vector of the same length as x, where detected outliers have been replaced with NA.

See Also

detect_outliers_mad for the underlying outlier detection

Examples

# Clean parameter values
params <- c(0.01, 0.012, 0.011, 0.1, 0.009, 0.011, 0.15)
clean_params <- clean_data(params)

# Clean multiple parameter columns
param_table <- data.frame(
  k0 = runif(100),
  cooling_rate = runif(100),
  c_repulsion = runif(100)
)
clean_table <- as.data.frame(lapply(param_table, clean_data))


[Package topolow version 1.0.0 Index]