Standardizes a numeric vector by centering it to have a mean of 0
and scaling it to have a standard deviation of 1.
Usage
norm_zscore(x, na.rm = TRUE)
Arguments
- x
A numeric vector.
- na.rm
Logical. Should NA values be removed during mean/sd calculation?
Default is TRUE.
Value
A numeric vector.
If the input vector has zero variance (all values are identical),
the function returns a centered vector (all zeros) and issues a warning.
Details
Formula: \(z = \frac{x - \mu}{\sigma}\)
References
Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques (3rd ed.). Morgan Kaufmann.
Examples
# Standard usage
norm_zscore(c(1, 2, 3, 4, 5))
#> [1] -1.2649111 -0.6324555 0.0000000 0.6324555 1.2649111
# Edge case: Zero variance
norm_zscore(c(5, 5, 5))
#> Warning: Standard deviation is zero. Returning centered vector (zeros).
#> [1] 0 0 0
