arXiv:2504.00001 · v2

HistogramTools for Efficient Data Analysis and Distribution Representation in Large Data Sets

首次提交 2025-02-05 10:47

版本更新 2026-11-11 04:59

雷达观测 2026-11-13 11:12

摘要

Histograms provide a powerful means of summarizing large data sets by representing their distribution in a compact, binned form. The HistogramTools R package enhances R built-in histogram functionality, offering advanced methods for manipulating and analyzing histograms, especially in large-scale data environments. Key features include the ability to serialize histograms using Protocol Buffers for distributed computing tasks, tools for merging and modifying histograms, and techniques for measuring and visualizing information loss in histogram representations. The package is particularly suited for environments utilizing MapReduce, where efficient storage and data sharing are critical. This paper presents various methods of histogram bin manipulation, distance measures, quantile approximation, and error estimation in cumulative distribution functions (CDFs) derived from histograms. Visualization techniques and efficient storage representations are also discussed alongside applications for large data processing and distributed computing tasks.

作者备注：arXiv admin note: This version has been withdrawn by arXiv administrators due to inappropriate text reuse from external sources