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V. Shanmugaraj,G. Shruthi,Arun Kumar Shettigar,Prasad Krishna mutually reinforcing, because MCMC methods are often necessary for the practical implementation of spatial statistical inference, while new spatial stochastic models in turn motivate the development of improved MCMC algorithms. This volume shows how sophisticated spatial statistical and computation

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S. Padmanabhan,T. Vinod Kumar,V. Muthuraman,D. Sendil Kumar,Mulinti Navneeth Reddy,T. Adi Sesha Sai is and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data  (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data  (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox

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