IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2006i2p1163-1183.html
   My bibliography  Save this article

A novel method for testing normality in a mixed model of a nested classification

Author

Listed:
  • Hwang, Yi-Ting
  • Wei, Peir Feng

Abstract

No abstract is available for this item.

Suggested Citation

  • Hwang, Yi-Ting & Wei, Peir Feng, 2006. "A novel method for testing normality in a mixed model of a nested classification," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1163-1183, November.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:2:p:1163-1183
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(05)00307-5
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. J. P. Royston, 1982. "The W Test for Normality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(2), pages 176-180, June.
    2. Paul Zhang, 1999. "Omnibus test of normality using the Q statistic," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(4), pages 519-528.
    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. Wangli Xu & Yanwen Li & Dawo Song, 2013. "Testing normality in mixed models using a transformation method," Statistical Papers, Springer, vol. 54(1), pages 71-84, February.
    2. Gerda Claeskens & Jeffrey Hart, 2009. "Goodness-of-fit tests in mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 213-239, August.

    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. Minguez, Ana & Javier Sese, F., 2022. "Why do you want a relationship, anyway? Consent to receive marketing communications and donors’ willingness to engage with nonprofits," Journal of Business Research, Elsevier, vol. 148(C), pages 356-367.
    2. Lada, Emily K. & Wilson, James R., 2006. "A wavelet-based spectral procedure for steady-state simulation analysis," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1769-1801, November.
    3. Gustavo Castilho Beruski & Luis Miguel Schiebelbein & André Belmont Pereira, 2020. "Maize Yield Components as Affected by Plant Population, Planting Date and Soil Coverings in Brazil," Agriculture, MDPI, vol. 10(12), pages 1-20, November.
    4. Ali Derakhshan Asl & Kuan Yew Wong & Manoj Kumar Tiwari, 2016. "Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy, particle swarm optimisation, and genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 799-823, February.
    5. repec:ers:journl:v:volumexxi:y:2018:i:issue4:p:622-636 is not listed on IDEAS
    6. Lauren Bin Dong & David E. A. Giles, 2004. "An Empirical Likelihood Ratio Test for Normality," Econometrics Working Papers 0401, Department of Economics, University of Victoria.
    7. Anthony Medford & James W. Vaupel, 2020. "Extremes are not normal: a reminder to demographers," Journal of Population Research, Springer, vol. 37(1), pages 91-106, March.
    8. Wangli Xu & Yanwen Li & Dawo Song, 2013. "Testing normality in mixed models using a transformation method," Statistical Papers, Springer, vol. 54(1), pages 71-84, February.
    9. Vexler, Albert & Gurevich, Gregory, 2010. "Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 531-545, February.
    10. Shalit, Haim, 2012. "Using OLS to test for normality," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2050-2058.
    11. Shah, Chandra, 1997. "Model selection in univariate time series forecasting using discriminant analysis," International Journal of Forecasting, Elsevier, vol. 13(4), pages 489-500, December.
    12. Predrag Petrović & Goran Nikolić, 2018. "Schumpeterian Growth Theory: Empirical Testing Of Barriers To Competition-Proximity To Frontier Algorithm," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 63(217), pages 7-38, April – J.
    13. Seongmin Kang & Jeahyung Cha & Changsang Cho & Ki-Hyun Kim & Eui-Chan Jeon, 2020. "Estimation of appropriate CO2 concentration sampling cycle for MSW incinerators," Energy & Environment, , vol. 31(3), pages 535-544, May.
    14. Tomasz Górecki & Lajos Horváth & Piotr Kokoszka, 2020. "Tests of Normality of Functional Data," International Statistical Review, International Statistical Institute, vol. 88(3), pages 677-697, December.
    15. Yang, J. & Greenwood, D. J. & Rowell, D. L. & Wadsworth, G. A. & Burns, I. G., 2000. "Statistical methods for evaluating a crop nitrogen simulation model, N_ABLE," Agricultural Systems, Elsevier, vol. 64(1), pages 37-53, April.
    16. Jurgita Arnastauskaitė & Tomas Ruzgas & Mindaugas Bražėnas, 2021. "An Exhaustive Power Comparison of Normality Tests," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
    17. repec:dau:papers:123456789/2714 is not listed on IDEAS
    18. Amir Abolhassani & Gale Boyd & Majid Jaridi & Bhaskaran Gopalakrishnan & James Harner, 2023. "“Is Energy That Different from Labor?” Similarity in Determinants of Intensity for Auto Assembly Plants," Energies, MDPI, vol. 16(4), pages 1-35, February.
    19. Lai Zhi Yong & Siti Khairunniza-Bejo & Mahirah Jahari & Farrah Melissa Muharam, 2022. "Automatic Disease Detection of Basal Stem Rot Using Deep Learning and Hyperspectral Imaging," Agriculture, MDPI, vol. 13(1), pages 1-16, December.
    20. Carl H. Korkpoe & Peterson Owusu Junior, 2018. "Behaviour of Johannesburg Stock Exchange All Share Index Returns - An Asymmetric GARCH and News Impact Effects Approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 68(1), pages 26-42, January-M.
    21. Katsaprakakis, Dimitris Al. & Papadakis, Nikos & Kozirakis, George & Minadakis, Yiannis & Christakis, Dimitris & Kondaxakis, Konstantinos, 2009. "Electricity supply on the island of Dia based on renewable energy sources (R.E.S.)," Applied Energy, Elsevier, vol. 86(4), pages 516-527, April.
    22. Manuel Denzer & Constantin Weiser, 2021. "Beyond F-statistic - A General Approach for Assessing Weak Identification," Working Papers 2107, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.

    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:eee:csdana:v:51:y:2006:i:2:p:1163-1183. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.