Selection of statistical technique for imputation of single site-univariate and multisite–multivariate methods for particulate pollutants time series data with long gaps and high missing percentage-Reference-Cited by-同舟云学术

Selection of statistical technique for imputation of single site-univariate and multisite–multivariate methods for particulate pollutants time series data with long gaps and high missing percentage

Published:2023-05-23 Issue:30 Volume:30 Page:75469-75488
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

K Priti,Shakya Kaushlesh Singh,Kumar Prashant^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-27659-x.pdf

Reference73 articles.

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2. Agbailu AO, Seno A, Clement OO (2020) Kalman filter algorithm versus other methods of estimating missing values: time series evidence. Studies 4(2):1–9

3. Allison P (2015) Imputation by predictive mean matching: promise & peril. Statistical Horizons

4. Allison PD (2001) Missing data. Sage publications

5. Aslan S (2010) Comparison of missing value imputation methods for meteorological time series data. MS thesis, Middle East Technical University

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