GKNNGereformeerde Kerk Nieuweroord Noordscheschut (Dutch: Reformed Church of New Roord Noordscheschut)
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Thus the GkNN method does not make accurate detailed month by month predictions of the yield.
Variance of the Average Annual Yield Predicted by GkNN Simulation
as R [right arrow][infinity] (assuming that the index selection at Step (3) of the GkNN algorithm at time t is independent of its selection at time s).
and so the variance of the predicted annual average annual yield as computed by the GkNN method tends to zero as the total number of years m in the simulation increases.
Thus the computation of average annual yield using GkNN seems to be well behaved.
Consider the GkNN process defined by training data {([w.sub.i,] [u.sub.i)] : i = 1, ..., N} [subset] V x [0, [infinity]).
It follows that the GkNN process is stochastically dependent on {[v.sub.t] : t = 1,2, ...} with kernel K defined by
Let {[z.sub.t] : t = 1,2, ...} be a realization (replicate) of {[y.sub.t] : t = 1,2, ...} and let KN be the kernel associated with the GkNN process with training set [W.sub.N] = {([v.sub.i, [z.sub.i)]] : i = 1, ..., N} and probabilities
Thus the GkNN kernel equals the kernel of the dependent process in the sense defined above as long as the training set for the GkNN process is large enough.