IDEAS home Printed from https://ideas.repec.org/a/spr/alstar/v96y2012i1p1-23.html
   My bibliography  Save this article

Principal component analysis with interval imputed missing values

Author

Listed:
  • Paola Zuccolotto

Abstract

No abstract is available for this item.

Suggested Citation

  • Paola Zuccolotto, 2012. "Principal component analysis with interval imputed missing values," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 1-23, January.
  • Handle: RePEc:spr:alstar:v:96:y:2012:i:1:p:1-23
    DOI: 10.1007/s10182-011-0164-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10182-011-0164-3
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10182-011-0164-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael E. Tipping & Christopher M. Bishop, 1999. "Probabilistic Principal Component Analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 611-622.
    2. Billard L. & Diday E., 2003. "From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 470-487, January.
    3. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
    4. Federica Gioia & Carlo Lauro, 2006. "Principal component analysis on interval data," Computational Statistics, Springer, vol. 21(2), pages 343-363, June.
    5. Louis Guttman, 1954. "Some necessary conditions for common-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(2), pages 149-161, June.
    6. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Angela Blanco-Fernández & Peter Winker, 2016. "Data generation processes and statistical management of interval data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 475-494, October.

    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.
    1. Marconi, Gabriele, 2014. "European higher education policies and the problem of estimating a complex model with a small cross-section," MPRA Paper 87600, University Library of Munich, Germany.
    2. Iyetomi, Hiroshi & Nakayama, Yasuhiro & Yoshikawa, Hiroshi & Aoyama, Hideaki & Fujiwara, Yoshi & Ikeda, Yuichi & Souma, Wataru, 2011. "What causes business cycles? Analysis of the Japanese industrial production data," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 246-272, September.
    3. Sergio Camiz & Valério D. Pillar, 2018. "Identifying the Informational/Signal Dimension in Principal Component Analysis," Mathematics, MDPI, vol. 6(11), pages 1-16, November.
    4. Leise Kelli de Oliveira & Carla de Oliveira Leite Nascimento & Paulo Renato de Sousa & Paulo Tarso Vilela de Resende & Francisco Gildemir Ferreira da Silva, 2019. "Transport Service Provider Perception of Barriers and Urban Freight Policies in Brazil," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    5. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Jun 2024.
    6. Psaradakis, Zacharias & Vávra, Marián, 2014. "On testing for nonlinearity in multivariate time series," Economics Letters, Elsevier, vol. 125(1), pages 1-4.
    7. Qingyong Wang & Hong-Ning Dai & Hao Wang, 2017. "A Smart MCDM Framework to Evaluate the Impact of Air Pollution on City Sustainability: A Case Study from China," Sustainability, MDPI, vol. 9(6), pages 1-17, May.
    8. Aaron Fisher & Brian Caffo & Brian Schwartz & Vadim Zipunnikov, 2016. "Fast, Exact Bootstrap Principal Component Analysis for > 1 Million," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 846-860, April.
    9. Jung, WoongHee & Taflanidis, Alexandros A. & Kyprioti, Aikaterini P. & Zhang, Jize, 2024. "Adaptive multi-fidelity Monte Carlo for real-time probabilistic storm surge predictions," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    10. Michael Greenacre & Patrick J. F Groenen & Trevor Hastie & Alfonso Iodice d’Enza & Angelos Markos & Elena Tuzhilina, 2023. "Principal component analysis," Economics Working Papers 1856, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Marco Carrer & Renzo Motta & Paola Nola, 2012. "Significant Mean and Extreme Climate Sensitivity of Norway Spruce and Silver Fir at Mid-Elevation Mesic Sites in the Alps," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-9, November.
    12. Giuseppe D'Onza & Alessandra Rigolini & Francesco Brotini, 2016. "Esiste una strategia di Internal Auditing che crea valore? Un?analisi empirica del contesto italiano," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2016(1), pages 125-148.
    13. Kelly P. Murillo & Eugenio M. Rocha, 2020. "Factors Influencing the Economic Behavior of the Food, Beverages and Tobacco Industry: A Case Study for Portuguese Enterprises," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 6(2), pages 99-121, December.
    14. Francesco Curreri & Giacomo Fiumara & Maria Gabriella Xibilia, 2020. "Input Selection Methods for Soft Sensor Design: A Survey," Future Internet, MDPI, vol. 12(6), pages 1-24, June.
    15. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
    16. Gaofeng Jia & Alexandros Taflanidis & Norberto Nadal-Caraballo & Jeffrey Melby & Andrew Kennedy & Jane Smith, 2016. "Surrogate modeling for peak or time-dependent storm surge prediction over an extended coastal region using an existing database of synthetic storms," 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. 81(2), pages 909-938, March.
    17. Dorota Toczydlowska & Gareth W. Peters & Man Chung Fung & Pavel V. Shevchenko, 2017. "Stochastic Period and Cohort Effect State-Space Mortality Models Incorporating Demographic Factors via Probabilistic Robust Principal Components," Risks, MDPI, vol. 5(3), pages 1-77, July.
    18. Joy R. Petway & Yu-Pin Lin & Rainer F. Wunderlich, 2019. "Analyzing Opinions on Sustainable Agriculture: Toward Increasing Farmer Knowledge of Organic Practices in Taiwan-Yuanli Township," Sustainability, MDPI, vol. 11(14), pages 1-27, July.
    19. Chen, Tao & Martin, Elaine & Montague, Gary, 2009. "Robust probabilistic PCA with missing data and contribution analysis for outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3706-3716, August.
    20. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.

    Corrections

    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:spr:alstar:v:96:y:2012:i:1:p:1-23. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.