maxKS0

MaxKS0 is a statistical metric used in comparative distribution analysis. It denotes the maximum observed value of the Kolmogorov–Smirnov (KS) distance under a baseline condition labeled zero (0). In practice, maxKS0 is computed when multiple KS comparisons are made between a sample and a baseline distribution across a set of features, time points, or bootstrap resamples. Formally, if D_i denotes the KS distance for the i-th comparison, then maxKS0 = max_i D_i. The “0” subscript reflects a baseline or null condition against which deviations are measured.

Computationally, maxKS0 involves calculating the KS distance for each comparison of interest and then selecting the largest value. This makes it a summary statistic that captures the strongest observed deviation from the baseline across a collection of tests or moments. It is commonly used in workflows that monitor distributional similarity over multiple dimensions, time periods, or resampling iterations.

Applications of maxKS0 include drift detection in time-series data, quality control in manufacturing processes, and goodness-of-fit assessments where several features or periods are tested against a common baseline. Interpreting maxKS0 relies on comparing the metric to a predefined threshold; values above the threshold indicate substantial deviation from the baseline distribution and may prompt further investigation.

Limitations include sensitivity to sample size and the potential to mask localized changes by aggregating them into a single maximum. As with other KS-based measures, discrete data and tied observations require careful handling. Related concepts include the Kolmogorov–Smirnov statistic, KS tests, bootstrap methods, and permutation testing.

See also: Kolmogorov–Smirnov test, KS statistic, drift detection, bootstrap, permutation test.