Eesmärgiks on leida muutuja Z parim lineaarne nihketa hinnang (best linear unbiased estimate – BLUE) iga ruumipunkti j jaoks. See on parim ruuthälvete minimeerimise, lineaarne lineaarse autoregressioonimudeli kasutamise (hinnangud on vaatluste kaalutud lineaarkombinatsioonid) ning hälbeta prognooside ja empiiriliste vaatluste keskväärtuste kokkulangevuse mõttes.
The interpolation methods developed by Matheron, Krige, and their co-workers are optimal in the sense that the interpolation weights are chosen so as to optimize the interpolation function, i.e. to provide a Best Linear Unbiased Estimate (BLUE) of the value of a variable at a given point.
The interpolation methods developed by Matheron, Krige, and their co-workers are optimal in the sense that the interpolation weights are chosen so as to optimize the interpolation function, i.e. to provide a Best Linear Unbiased Estimate (BLUE) of the value of a variable at a given point.
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