Variogram analysis of stochastic processes
Keywords:
stochastic process, intrinsic stationarity, semivariogram, confidence intervalAbstract
Properties of the semivariogram of an intrinsically stationary continuous-time random process with finite second moment are investigated. A necessary and sufficient conditions for a continuous function to be semivariogram are found. Confidence intervals for the semivariogram of Gaussian stationary stochastic process are defined. Properties of ꭓ2-distribution are used for constructing confidence intervals for semivariogram. The proposed confidence intervals are more informative compared with point estimates of the semivariogram.
References
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