IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v8y2006i1p97-108.html
   My bibliography  Save this article

Multilevel models for analyzing people’s daily movement behavior

Author

Listed:
  • Matteo Bottai
  • Nicola Salvati
  • Nicola Orsini

Abstract

No abstract is available for this item.

Suggested Citation

  • Matteo Bottai & Nicola Salvati & Nicola Orsini, 2006. "Multilevel models for analyzing people’s daily movement behavior," Journal of Geographical Systems, Springer, vol. 8(1), pages 97-108, March.
    • Handle: RePEc:kap:jgeosy:v:8:y:2006:i:1:p:97-108
    DOI: 10.1007/s10109-006-0017-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10109-006-0017-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10109-006-0017-x?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. Matteo Bottai & Nicola Orsini, 2004. "Confidence intervals for the variance component of random-effects linear models," Stata Journal, StataCorp LP, vol. 4(4), pages 429-435, December.
    2. Matteo Bottai, 2003. "Confidence regions when the Fisher information is zero," Biometrika, Biometrika Trust, vol. 90(1), pages 73-84, March.
    3. R.W. Vickerman, 1984. "Urban and Regional Change, Migration and Commuting — The Dynamics of Workplace, Residence and Transport Choice," Urban Studies, Urban Studies Journal Limited, vol. 21(1), pages 15-29, February.
    4. Ciprian M. Crainiceanu & David Ruppert, 2004. "Likelihood ratio tests in linear mixed models with one variance component," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 165-185, February.
    5. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, October.
    6. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, October.
    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. Cecilia Olivieri & Xavier Fageda, 2019. "Determinants of urban mobility with a focus on gender: a multilevel analysis in the Metropolitan Area of Montevideo, Uruguay," Documentos de Trabajo (working papers) 0419, Department of Economics - dECON.
    2. Tae-Hyoung Tommy Gim, 2017. "Full Random Coefficients Multilevel Modeling of the Relationship between Land Use and Trip Time on Weekdays and Weekends," Sustainability, MDPI, vol. 9(10), pages 1-26, October.
    3. Olivieri, Cecilia & Fageda, Xavier, 2021. "Urban mobility with a focus on gender: The case of a middle-income Latin American city," Journal of Transport Geography, Elsevier, vol. 91(C).
    4. Mercado, Ruben & Páez, Antonio, 2009. "Determinants of distance traveled with a focus on the elderly: a multilevel analysis in the Hamilton CMA, Canada," Journal of Transport Geography, Elsevier, vol. 17(1), pages 65-76.
    5. Jinhyun Hong & Qing Shen & Lei Zhang, 2014. "How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales," Transportation, Springer, vol. 41(3), pages 419-440, May.
    6. Zhang, Lei & Hong, Jin Hyun & Nasri, Arefeh & Shen, Qing, 2012. "How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 40-52.

    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. Zanin, Luca & Marra, Giampiero, 2012. "Assessing the functional relationship between CO2 emissions and economic development using an additive mixed model approach," Economic Modelling, Elsevier, vol. 29(4), pages 1328-1337.
    2. Sonja Greven & Ciprian Crainiceanu, 2013. "On likelihood ratio testing for penalized splines," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 387-402, October.
    3. Oliver E. Lee & Thomas M. Braun, 2012. "Permutation Tests for Random Effects in Linear Mixed Models," Biometrics, The International Biometric Society, vol. 68(2), pages 486-493, June.
    4. Chen, Haiqiang & Fang, Ying & Li, Yingxing, 2015. "Estimation And Inference For Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines," Econometric Theory, Cambridge University Press, vol. 31(4), pages 753-777, August.
    5. repec:wyi:journl:002195 is not listed on IDEAS
    6. Huaihou Chen & Yuanjia Wang, 2011. "A Penalized Spline Approach to Functional Mixed Effects Model Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 861-870, September.
    7. Philip T. Reiss & R. Todd Ogden, 2010. "Functional Generalized Linear Models with Images as Predictors," Biometrics, The International Biometric Society, vol. 66(1), pages 61-69, March.
    8. Andrada Ivanescu & Ana-Maria Staicu & Fabian Scheipl & Sonja Greven, 2015. "Penalized function-on-function regression," Computational Statistics, Springer, vol. 30(2), pages 539-568, June.
    9. Sonja Greven & Fabian Scheipl, 2016. "Comment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1568-1573, October.
    10. Kruse, René-Marcel & Silbersdorff, Alexander & Säfken, Benjamin, 2022. "Model averaging for linear mixed models via augmented Lagrangian," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    11. Padoan, S.A. & Wand, M.P., 2008. "Mixed model-based additive models for sample extremes," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2850-2858, December.
    12. Takumi Saegusa & Chongzhi Di & Ying Qing Chen, 2014. "Hypothesis testing for an extended cox model with time-varying coefficients," Biometrics, The International Biometric Society, vol. 70(3), pages 619-628, September.
    13. Sumanta Adhya & Tathagata Banerjee & Gaurangadeb Chattopadhyay, 2012. "Inference on finite population categorical response: nonparametric regression-based predictive approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 69-98, January.
    14. Huaihou Chen & Philip T. Reiss & Thaddeus Tarpey, 2014. "Optimally weighted L-super-2 distance for functional data," Biometrics, The International Biometric Society, vol. 70(3), pages 516-525, September.
    15. Vanesa Jordá & José Sarabia, 2015. "International Convergence in Well-Being Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 120(1), pages 1-27, January.
    16. Ugarte, M.D. & Goicoa, T. & Militino, A.F. & Durbán, M., 2009. "Spline smoothing in small area trend estimation and forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3616-3629, August.
    17. Philip T. Reiss & Lei Huang & Pei‐Shien Wu & Huaihou Chen & Stan Colcombe, 2017. "Pointwise influence matrices for functional‐response regression," Biometrics, The International Biometric Society, vol. 73(4), pages 1092-1101, December.
    18. Ghosal, Rahul & Maity, Arnab, 2022. "A Score Based Test for Functional Linear Concurrent Regression," Econometrics and Statistics, Elsevier, vol. 21(C), pages 114-130.
    19. Yuanjia Wang & Huaihou Chen, 2012. "On Testing an Unspecified Function Through a Linear Mixed Effects Model with Multiple Variance Components," Biometrics, The International Biometric Society, vol. 68(4), pages 1113-1125, December.
    20. Philip T. Reiss & R. Todd Ogden, 2009. "Smoothing parameter selection for a class of semiparametric linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 505-523, April.
    21. Annie Qu & Runze Li, 2006. "Quadratic Inference Functions for Varying-Coefficient Models with Longitudinal Data," Biometrics, The International Biometric Society, vol. 62(2), pages 379-391, June.

    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:kap:jgeosy:v:8:y:2006:i:1:p:97-108. 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.