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Geographically weighted small area methods have been studied in literature for small area estimation. Although these approaches are useful for the estimation of small area means efficiently under strict parametric assumptions, they can be very sensitive to outliers in the data. In this paper, we...
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We propose a new estimation methodology to address the presence of covariate measurement error by exploiting the availability of spatial data. The approach uses neighboring observations as repeated measurements, after suitably controlling for the random distance between the observations in a way...
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Cover -- Half Title -- Series -- Title -- Copyright -- Contents -- List of figures -- List of tables -- List of contributors -- Introduction -- Statement by the American Statistical Association on statistical significance and p-value - use in the book -- Acknowledgements -- 1 Basic operations in...
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problem of spatial statistics -- 1.3. Spatial sampling perspectives -- 1.4. Models of spatial autocorrelation -- 1.5. Towards ….9. References -- 5. Spatial autocorrelation and spectral analysis -- 5.1. A brief background for spectral analysis -- 5 … spatial dependence -- 8.1. A multivariate normal probability density function with spatial autocorrelation -- 8.2. Discerning …
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