Pseudo-random reference sequences with Mersenne Twister (2^19937-1) using GNU Octave. Mastrave project technical report

Computationally intensive numerical tasks such as those involving statistical resampling require robust algorithms for generating large sequences of pseudo-random numbers. Where the amount of data to be processed is relatively moderate, the paradigm of reproducible research is in principle suitable to be applied not only to algorithms, free software, data and metadata, but also to the involved pseudo-random sequences themselves. However, finding reference sequences of pseudo random numbers suitable to enable such a deep reproducibility may be surprisingly difficult. Here, sequences suitable to be used as reference uniformly distributed pseudo-random datasets are presented. The dataset of sequences has been generated using Mersenne Twister with a period of 2^19937-1, as implemented in GNU Octave (version 3.6.1) with the Mastrave modelling library. The sequences are available in plain text format and also in the format MATLAB version 7, which is portable in both GNU Octave and MATLAB computing environments.

诸如统计重采样这类计算密集型数值任务，需要借助稳健的算法生成大规模伪随机数序列。当待处理数据体量相对适中时，可重复研究（reproducible research）范式原则上不仅可应用于算法、自由软件、数据与元数据，还可覆盖所涉及的伪随机序列本身。然而，要获取适配此类深度可复现性要求的伪随机数参考序列，其难度往往出人意料。本文提供了可作为参考基准的均匀分布伪随机数据集序列。该序列数据集采用周期为2^19937-1的梅森旋转算法（Mersenne Twister）生成，具体实现基于搭载Mastrave建模库的GNU Octave（版本3.6.1）。该序列支持纯文本格式与MATLAB 7格式两种存储形式，可在GNU Octave与MATLAB计算环境中通用兼容。