Principal Component Regression Modeling and Analysis of PM 10 and Meteorological Parameters in Sarajevo with and without Temperature Inversion
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ian T. Jolliffe, 1982. "A Note on the Use of Principal Components in Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 300-303, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Minjung Kyung & Ju-Hyun Park & Ji Yeh Choi, 2022. "Bayesian Mixture Model of Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 946-966, September.
- Hugh L. Christensen, 2015. "Algorithmic arbitrage of open-end funds using variational Bayes," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-38, December.
- Jiaju Miao & Pawel Polak, 2023. "Online Ensemble of Models for Optimal Predictive Performance with Applications to Sector Rotation Strategy," Papers 2304.09947, arXiv.org.
- Elkin Castaño & Santiago Gallón, 2017. "A solution for multicollinearity in stochastic frontier production function models," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 9-23, Enero - J.
- Ranjith Vijayakumar & Ji Yeh Choi & Eun Hwa Jung, 2022. "A Unified Neural Network Framework for Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1503-1528, December.
- Anish Agarwal & Keegan Harris & Justin Whitehouse & Zhiwei Steven Wu, 2023. "Adaptive Principal Component Regression with Applications to Panel Data," Papers 2307.01357, arXiv.org, revised Oct 2023.
- Santiago Velásquez & Juho Kanniainen & Saku Mäkinen & Jaakko Valli, 2018. "Layoff announcements and intra-day market reactions," Review of Managerial Science, Springer, vol. 12(1), pages 203-228, January.
- Sandip Garai & Ranjit Kumar Paul & Debopam Rakshit & Md Yeasin & Walid Emam & Yusra Tashkandy & Christophe Chesneau, 2023. "Wavelets in Combination with Stochastic and Machine Learning Models to Predict Agricultural Prices," Mathematics, MDPI, vol. 11(13), pages 1-18, June.
- Luis A. Barboza & Julien Emile-Geay & Bo Li & Wan He, 2019. "Efficient Reconstructions of Common Era Climate via Integrated Nested Laplace Approximations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 535-554, September.
- Israel R. Orimoloye & Adeyemi O. Olusola & Johanes A. Belle & Chaitanya B. Pande & Olusola O. Ololade, 2022. "Drought disaster monitoring and land use dynamics: identification of drought drivers using regression-based algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(2), pages 1085-1106, June.
- Tanin Sirimongkolkasem & Reza Drikvandi, 2019. "On Regularisation Methods for Analysis of High Dimensional Data," Annals of Data Science, Springer, vol. 6(4), pages 737-763, December.
- Paweł Teisseyre & Robert A. Kłopotek & Jan Mielniczuk, 2016. "Random Subspace Method for high-dimensional regression with the R package regRSM," Computational Statistics, Springer, vol. 31(3), pages 943-972, September.
- Eric Jacobson, 2021. "Who Votes for Library Bonds? A Principal Component Exploration," Papers 2107.01095, arXiv.org.
- Bittencourt, Manoel & Gupta, Rangan & Stander, Lardo, 2014.
"Tax evasion, financial development and inflation: Theory and empirical evidence,"
Journal of Banking & Finance, Elsevier, vol. 41(C), pages 194-208.
- Manoel Bittencourt & Rangan Gupta & Lardo Stander, 2013. "Tax evasion, financial development and inflation: theory and empirical evidence," Working Papers 201316, University of Pretoria, Department of Economics.
- Sondes Gharsellaoui & Majdi Mansouri & Shady S. Refaat & Haitham Abu-Rub & Hassani Messaoud, 2020. "Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches," Energies, MDPI, vol. 13(3), pages 1-16, January.
- Ryuta Tamura & Ken Kobayashi & Yuichi Takano & Ryuhei Miyashiro & Kazuhide Nakata & Tomomi Matsui, 2019. "Mixed integer quadratic optimization formulations for eliminating multicollinearity based on variance inflation factor," Journal of Global Optimization, Springer, vol. 73(2), pages 431-446, February.
- Anish Agarwal & Devavrat Shah & Dennis Shen, 2020. "Synthetic Interventions," Papers 2006.07691, arXiv.org, revised Oct 2023.
- Castano, Elkin & Gallon, Santiago, 2016. "A solution for multicollinearity in stochastic frontier production function models," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 86, pages 9-23, December.
- Alamgir Kabir & Md Jahanur Rahman & Abu Ahmed Shamim & Rolf D W Klemm & Alain B Labrique & Mahbubur Rashid & Parul Christian & Keith P West Jr., 2017. "Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
- Maurizio Carpita & Paola Pasca & Serena Arima & Enrico Ciavolino, 2023. "Clustering of variables methods and measurement models for soccer players’ performances," Annals of Operations Research, Springer, vol. 325(1), pages 37-56, June.
More about this item
Keywords
principal component regression; environmental and spatiotemporal statistics; temperature inversion; air quality and pollution; PM 10 ; meteorological parameters;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11230-:d:1197149. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.