Estimating variance under interval and fuzzy uncertainty: Parallel algorithms

Villaverde, Karen; Xiang, Gang

doi:10.1109/fuzzy.2008.4630496

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…The two basic directions of research work are worth mentioning. The first one includes online calculation methods developed by Kreinovich et al (2007), Pébay (2008), Villaverde and Xiang (2008) and Terriberry (2008). The second one involves parallel data processing methods proposed by Schubert et al (2015), Schubert and Gertz (2018) and Gouin et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Algorithm for error-free determination of the variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data

Chmielowiec

2021

Comput Stat

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The article presents an algorithm for fast and error-free determination of statistics such as the arithmetic mean and variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data. Additionally, it shows that both floating-point and integer representation can be used to perform this kind of statistical calculations. The author proves a theorem on the number of bits of precision that an arithmetic type must have to guarantee error-free determination of the arithmetic mean and variance. The article also presents the extension of Welford’s formula for determining variance for the sliding window method—determining the variance of fixed-length contiguous subsequences. The section dedicated to implementation tests shows the running times of individual algorithms depending on the arithmetic type used. The research shows that the use of integers in calculations makes the determination of the aforementioned statistics much faster.

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Section: Introductionmentioning

confidence: 99%

Algorithm for error-free determination of the variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data

Chmielowiec

2021

Comput Stat

View full text Add to dashboard Cite

show abstract

Estimating variance under interval and fuzzy uncertainty: Parallel algorithms

Cited by 1 publication

References 12 publications

Algorithm for error-free determination of the variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data

Algorithm for error-free determination of the variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data

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