randbanding

Randbanding is a data-analysis technique in statistics and data visualization that involves partitioning the range of a quantitative variable into a set of random intervals, or bands. Unlike fixed-bin methods, randbanding defines the boundaries of the bands stochastically, resulting in bands that may vary in width across the range. The technique is used to study how summaries and patterns change when data are grouped by randomly defined ranges, and to support exploratory analysis and simulation-based assessment.

Procedure: For a variable with observed values, select the desired number of bands k and specify the overall range [min, max]. Generate k-1 random cut points within this range, then sort them to form k contiguous intervals. Each observation is assigned to the band corresponding to its value. The random banding process can be repeated to produce multiple independent realizations, enabling aggregation of results and assessment of variability across band definitions.

Applications: Randbanding is employed to investigate distributional properties within bands, test robustness of density or summary estimates to band boundaries, and create null models for band-based statistics. It can aid visualization by showing how statistical summaries vary as band boundaries shift, potentially revealing dependence on boundary placement that fixed-bin methods might obscure.

Variants and considerations: The choice of k and the distribution used to generate cut points influence outcomes. Randbanding can be sensitive to outliers at the range extremes, and multiple repetitions are often necessary to derive stable conclusions. When interpreting results, it should be compared to traditional binning approaches such as equal-width and equal-frequency binning.

See also: Binning, histogram, data visualization, adaptive binning, quantile binning.