IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v78y2016i3p563-587.html

Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy

Author

Listed:
  • Alexander Hartmann
  • Stephan Huckemann
  • Jörn Dannemann
  • Oskar Laitenberger
  • Claudia Geisler
  • Alexander Egner
  • Axel Munk

Abstract

No abstract is available for this item.

Suggested Citation

  • Alexander Hartmann & Stephan Huckemann & Jörn Dannemann & Oskar Laitenberger & Claudia Geisler & Alexander Egner & Axel Munk, 2016. "Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 563-587, June.
  • Handle: RePEc:bla:jorssb:v:78:y:2016:i:3:p:563-587
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssb.12128
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. H. Dette & A. Munk, 1998. "Testing heteroscedasticity in nonparametric regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(4), pages 693-708.
    2. J. Gower, 1975. "Generalized procrustes analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 33-51, March.
    3. Axel Munk & Nicolai Bissantz & Thorsten Wagner & Gudrun Freitag, 2005. "On difference‐based variance estimation in nonparametric regression when the covariate is high dimensional," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 19-41, February.
    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. Kathrin Bissantz & Nicolai Bissantz & Katharina Proksch, 2021. "Nonparametric detection of changes over time in image data from fluorescence microscopy of living cells," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 1001-1017, September.

    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. Meyners, Michael & Qannari, El Mostafa, 2001. "Relating principal component analysis on merged data sets to a regression approach," Technical Reports 2001,47, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Peter Hall & Joel L. Horowitz, 2012. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers CWP14/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Long Feng & Changliang Zou & Zhaojun Wang & Lixing Zhu, 2015. "Robust comparison of regression curves," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 185-204, March.
    4. Holger Dette & Kay Pilz, 2009. "On the estimation of a monotone conditional variance in nonparametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 111-141, March.
    5. Juliana Martins Ruzante & Valerie J. Davidson & Julie Caswell & Aamir Fazil & John A. L. Cranfield & Spencer J. Henson & Sven M. Anders & Claudia Schmidt & Jeffrey M. Farber, 2010. "A Multifactorial Risk Prioritization Framework for Foodborne Pathogens," Risk Analysis, John Wiley & Sons, vol. 30(5), pages 724-742, May.
    6. Barbara McGillivray & Gard B. Jenset & Khalid Salama & Donna Schut, 2022. "Investigating patterns of change, stability, and interaction among scientific disciplines using embeddings," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    7. Wei Wang & Stephen J Lycett & Noreen von Cramon-Taubadel & Jennie J H Jin & Christopher J Bae, 2012. "Comparison of Handaxes from Bose Basin (China) and the Western Acheulean Indicates Convergence of Form, Not Cognitive Differences," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, April.
    8. Zhu, Xuehu & Chen, Fei & Guo, Xu & Zhu, Lixing, 2016. "Heteroscedasticity testing for regression models: A dimension reduction-based model adaptive approach," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 263-283.
    9. Holger Dette & Mareen Marchlewski & Jens Wagener, 2012. "Testing for a constant coefficient of variation in nonparametric regression by empirical processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(5), pages 1045-1070, October.
    10. Lisa Sakamoto & Hiromi Kajiya-Kanegae & Koji Noshita & Hideki Takanashi & Masaaki Kobayashi & Toru Kudo & Kentaro Yano & Tsuyoshi Tokunaga & Nobuhiro Tsutsumi & Hiroyoshi Iwata, 2019. "Comparison of shape quantification methods for genomic prediction, and genome-wide association study of sorghum seed morphology," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-15, November.
    11. Mardia, Kanti V. & Wiechers, Henrik & Eltzner, Benjamin & Huckemann, Stephan F., 2022. "Principal component analysis and clustering on manifolds," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    12. Ibrahim, Muhammad Sohail & Dong, Wei & Yang, Qiang, 2020. "Machine learning driven smart electric power systems: Current trends and new perspectives," Applied Energy, Elsevier, vol. 272(C).
    13. John Gower & Garmt Dijksterhuis, 1994. "Multivariate analysis of coffee images: A study in the simultaneous display of multivariate quantitative and qualitative variables for several assessors," Quality & Quantity: International Journal of Methodology, Springer, vol. 28(2), pages 165-184, May.
    14. Holzmann, Hajo & Bissantz, Nicolai & Munk, Axel, 2007. "Density testing in a contaminated sample," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 57-75, January.
    15. Azhong Ye & Rob J Hyndman & Zinai Li, 2006. "Local Linear Multivariate Regression with Variable Bandwidth in the Presence of Heteroscedasticity," Monash Econometrics and Business Statistics Working Papers 8/06, Monash University, Department of Econometrics and Business Statistics.
    16. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    17. repec:ehu:biltok:5712 is not listed on IDEAS
    18. Peter Verboon & Willem Heiser, 1992. "Resistant orthogonal procrustes analysis," Journal of Classification, Springer;The Classification Society, vol. 9(2), pages 237-256, December.
    19. Holger Dette & Natalie Neumeyer & Ingrid Van Keilegom, 2007. "A new test for the parametric form of the variance function in non‐parametric regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 903-917, November.
    20. Grith, Maria & Härdle, Wolfgang Karl & Kneip, Alois & Wagner, Heiko, 2016. "Functional principal component analysis for derivatives of multivariate curves," SFB 649 Discussion Papers 2016-033, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Bissantz, Nicolai & Birke, Melanie, 2008. "Asymptotic normality and confidence intervals for inverse regression models with convolution-type operators," Technical Reports 2008,17, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssb:v:78:y:2016:i:3:p:563-587. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.