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Tests of homogeneity for spatial populations

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  • Cerioli, Andrea

Abstract

We consider the problem of testing the homogeneity hypothesis in an RxC contingency table when the data are spatially autocorrelated. We show that familiar asymptotic results are invalid under these circumstances and we propose a simple adjustment to the standard [chi]2 statistic that allows for spatial dependence.

Suggested Citation

  • Cerioli, Andrea, 2002. "Tests of homogeneity for spatial populations," Statistics & Probability Letters, Elsevier, vol. 58(2), pages 123-130, June.
    • Handle: RePEc:eee:stapro:v:58:y:2002:i:2:p:123-130
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    References listed on IDEAS

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    1. Andrea Cerioli, 2002. "Testing Mutual Independence Between Two Discrete-Valued Spatial Processes: A Correction to Pearson Chi-Squared," Biometrics, The International Biometric Society, vol. 58(4), pages 888-897, December.
    2. Wang, Kongming, 1994. "Solutions of the variational problem in the Curie--Weiss--Potts model," Stochastic Processes and their Applications, Elsevier, vol. 50(2), pages 245-252, April.
    3. De Dominicis, Rodolfo, 1983. "Asymptotic normal distribution of multidimensional statistics of dependent random variables," Journal of Multivariate Analysis, Elsevier, vol. 13(2), pages 302-309, June.
    4. Ellis, Richard S. & Wang, Kongming, 1990. "Limit theorems for the empirical vector of the Curie-Weiss-Potts model," Stochastic Processes and their Applications, Elsevier, vol. 35(1), pages 59-79, June.
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    Cited by:

    1. Andrea Cerioli, 2002. "Testing Mutual Independence Between Two Discrete-Valued Spatial Processes: A Correction to Pearson Chi-Squared," Biometrics, The International Biometric Society, vol. 58(4), pages 888-897, December.

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