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TESTING AREAL INTERPOLATION METHODS WITH US CENSUS 2010 DATA. (2014). Vanhems, Anne ; THOMAS-AGNAN, Christine.
In: Region et Developpement.
RePEc:tou:journl:v:40:y:2014:p:83-96.

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  1. Almquist Z. W. (2010). US Census spatial and demographic data in R: the UScensus2000 suite of packages. Journal of Statistical Software, 37, 1-31.

  2. Calcagno V., de Mazancourt C. (2010). glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models. Journal of Statistical Software, 34, 12.

  3. Do Van H., Thomas-Agnan C., Vanhems A. (2014). Accuracy of areal interpolation methods: Count data, preprint.
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  4. Do Van H., Thomas-Agnan C., Vanhems A. (2015). Spatial reallocation of areal data: a review, Revue d’Economie Régionale et Urbaine, Forthcoming.
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  5. Flowerdew R., Green M. (1992). Developments in areal interpolation methods and GIS, The Annals of Regional Science, 26, 67-78.

  6. Flowerdew R., Green M., Kehris E. (1991). Using areal interpolation methods in geographic information systems. Papers in Regional Science, Vol. 70, Issue 3, 303-315 Hastie T., Tibshirani R., Friedman J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition. Springer Series in Statistics. 2nd ed.

  7. Nous incluons également dans la comparaison la version normalisée de la régression dans le cas extensif introduit dans Do et al. (2015) et avec la version normalisée de la régression dans le cas intensif proposée ici. Finalement nous formulons quelques conseils pour choisir des variables auxiliaires. Mots-clés - INTERPOLATION DE DONNÉES SURFACIQUES, PROPRIÉTÉ PYCNOPHYLACTIQUE, DÉSAGRÉGATION SPATIALE
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