IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v140y2007i1p226-259.html
   My bibliography  Save this article

A spatial model for multivariate lattice data

Author

Listed:
  • Sain, Stephan R.
  • Cressie, Noel

Abstract

No abstract is available for this item.

Suggested Citation

  • Sain, Stephan R. & Cressie, Noel, 2007. "A spatial model for multivariate lattice data," Journal of Econometrics, Elsevier, vol. 140(1), pages 226-259, September.
    • Handle: RePEc:eee:econom:v:140:y:2007:i:1:p:226-259
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(06)00230-2
    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. Mardia, K. V., 1988. "Multi-dimensional multivariate Gaussian Markov random fields with application to image processing," Journal of Multivariate Analysis, Elsevier, vol. 24(2), pages 265-284, February.
    2. Xiaoping Jin & Bradley P. Carlin & Sudipto Banerjee, 2005. "Generalized Hierarchical Multivariate CAR Models for Areal Data," Biometrics, The International Biometric Society, vol. 61(4), pages 950-961, December.
    3. Alan Gelfand & Alexandra Schmidt & Sudipto Banerjee & C. Sirmans, 2004. "Nonstationary multivariate process modeling through spatially varying coregionalization," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 263-312, December.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2004. "Estimation of simultaneous systems of spatially interrelated cross sectional equations," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 27-50.
    5. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    6. Kim H. & Sun D. & Tsutakawa R.K., 2001. "A Bivariate Bayes Method for Improving the Estimates of Mortality Rates With a Twofold Conditional Autoregressive Model," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1506-1521, December.
    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. Li, Bo & Zhang, Hao, 2011. "An approach to modeling asymmetric multivariate spatial covariance structures," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1445-1453, November.
    2. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    3. Arnab Bhattacharjee & Eduardo Castro & Taps Maiti & João Marques, 2014. "Endogenous spatial structure and delineation of submarkets: A new framework with application to housing markets," SEEC Discussion Papers 1403, Spatial Economics and Econometrics Centre, Heriot Watt University.
    4. Ippoliti, L. & Martin, R.J. & Romagnoli, L., 2018. "Efficient likelihood computations for some multivariate Gaussian Markov random fields," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 185-200.
    5. Gupta, Abhimanyu, 2018. "Autoregressive spatial spectral estimates," Journal of Econometrics, Elsevier, vol. 203(1), pages 80-95.
    6. Noel Cressie & Andrew Zammit-Mangion, 2016. "Multivariate spatial covariance models: a conditional approach," Biometrika, Biometrika Trust, vol. 103(4), pages 915-935.
    7. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    8. Walguen Oscar & Jean Vaillant, 2021. "Cox Processes Associated with Spatial Copula Observed through Stratified Sampling," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
    9. Takahiro Yoshida & Morito Tsutsumi, 2018. "On the effects of spatial relationships in spatial compositional multivariate models," Letters in Spatial and Resource Sciences, Springer, vol. 11(1), pages 57-70, March.
    10. repec:esx:essedp:767 is not listed on IDEAS
    11. Ghulam A. Qadir & Carolina Euán & Ying Sun, 2021. "Flexible Modeling of Variable Asymmetries in Cross-Covariance Functions for Multivariate Random Fields," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(1), pages 1-22, March.
    12. Beran, Jan & Ghosh, Sucharita & Schell, Dieter, 2009. "On least squares estimation for long-memory lattice processes," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2178-2194, 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.
    1. Ying C. MacNab, 2018. "Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 497-541, September.
    2. Marco Gramatica & Peter Congdon & Silvia Liverani, 2021. "Bayesian modelling for spatially misaligned health areal data: A multiple membership approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 645-666, June.
    3. Takahiro Yoshida & Morito Tsutsumi, 2018. "On the effects of spatial relationships in spatial compositional multivariate models," Letters in Spatial and Resource Sciences, Springer, vol. 11(1), pages 57-70, March.
    4. Cindy Xin Feng, 2015. "Bayesian joint modeling of correlated counts data with application to adverse birth outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(6), pages 1206-1222, June.
    5. Xiaoping Jin & Sudipto Banerjee & Bradley P. Carlin, 2007. "Order‐free co‐regionalized areal data models with application to multiple‐disease mapping," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 817-838, November.
    6. Ippoliti, L. & Martin, R.J. & Romagnoli, L., 2018. "Efficient likelihood computations for some multivariate Gaussian Markov random fields," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 185-200.
    7. Douglas R. M. Azevedo & Marcos O. Prates & Dipankar Bandyopadhyay, 2021. "MSPOCK: Alleviating Spatial Confounding in Multivariate Disease Mapping Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 464-491, September.
    8. Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
    9. Brian J. Reich & James S. Hodges, 2008. "Modeling Longitudinal Spatial Periodontal Data: A Spatially Adaptive Model with Tools for Specifying Priors and Checking Fit," Biometrics, The International Biometric Society, vol. 64(3), pages 790-799, September.
    10. Salule Masangwi & Neil Ferguson & Anthony Grimason & Tracy Morse & Lawrence Kazembe, 2015. "The Pattern of Variation between Diarrhea and Malaria Coexistence with Corresponding Risk Factors in, Chikhwawa, Malawi: A Bivariate Multilevel Analysis," IJERPH, MDPI, vol. 12(7), pages 1-16, July.
    11. Areti Boulieri & Silvia Liverani & Kees Hoogh & Marta Blangiardo, 2017. "A space–time multivariate Bayesian model to analyse road traffic accidents by severity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 119-139, January.
    12. Mahmoud Torabi, 2014. "Hierarchical Bayesian bivariate disease mapping: analysis of children and adults asthma visits to hospital," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 612-621, March.
    13. Nicole H. Augustin & Stefan Lang & Monica Musio & Klaus Von Wilpert, 2007. "A spatial model for the needle losses of pine‐trees in the forests of Baden‐Württemberg: an application of Bayesian structured additive regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(1), pages 29-50, January.
    14. Wall, Melanie M. & Liu, Xuan, 2009. "Spatial latent class analysis model for spatially distributed multivariate binary data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3057-3069, June.
    15. Alexandra M. Schmidt, 2022. "Discussion on “Spatial+: a novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin," Biometrics, The International Biometric Society, vol. 78(4), pages 1300-1304, December.
    16. Miklos Arato, N. & Dryden, Ian L. & Taylor, Charles C., 2006. "Hierarchical Bayesian modelling of spatial age-dependent mortality," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1347-1363, November.
    17. Joaquim Henriques Vianna Neto & Alexandra M. Schmidt & Peter Guttorp, 2014. "Accounting for spatially varying directional effects in spatial covariance structures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 103-122, January.
    18. Song, J.J. & Ghosh, M. & Miaou, S. & Mallick, B., 2006. "Bayesian multivariate spatial models for roadway traffic crash mapping," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 246-273, January.
    19. Sudipto Banerjee & Gregg A. Johnson, 2006. "Coregionalized Single- and Multiresolution Spatially Varying Growth Curve Modeling with Application to Weed Growth," Biometrics, The International Biometric Society, vol. 62(3), pages 864-876, September.
    20. Xiaoping Jin & Bradley P. Carlin & Sudipto Banerjee, 2005. "Generalized Hierarchical Multivariate CAR Models for Areal Data," Biometrics, The International Biometric Society, vol. 61(4), pages 950-961, December.

    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:econom:v:140:y:2007:i:1:p:226-259. 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/jeconom .

    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.