Statistical analysis of the spatial distribution of fever in Burundi
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Kriging is a stochastic spatial interpolation method that predicts the value of a natural phenomenon at unsampled sites by an unbiased linear combination of minimum variances of observations of the phenomenon at nearby sites. This book is devoted to the comparison of spatial interpolation techniques. The mathematical foundations of these techniques are discussed. The resolution of the kriging equations is detailed and commented. The variographic analysis, which is a preliminary step to kriging, is also presented. The objective of this research is not only the deepening of the theory of kriging...
Kriging is a stochastic spatial interpolation method that predicts the value of a natural phenomenon at unsampled sites by an unbiased linear combination of minimum variances of observations of the phenomenon at nearby sites. This book is devoted to the comparison of spatial interpolation techniques. The mathematical foundations of these techniques are discussed. The resolution of the kriging equations is detailed and commented. The variographic analysis, which is a preliminary step to kriging, is also presented. The objective of this research is not only the deepening of the theory of kriging, but also the application of this theory to real data. Thus, a methodology for implementing kriging is proposed and illustrated using fever prevalence data in children under five in 2010 in Burundi. The results of kriging as a stochastic technique and of interpolation by the inverse weighted distance method as a deterministic technique are then compared using a statistical test.
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