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Covariogram estimation for the process contaminated with linear trend
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[QUOTE="New_Galatea, post: 1225538, member: 68013"] Let {S(t), t=1,2,...} be a zero-mean, unit variance, second-order stationary process in R^1, and define Y(t)=S(t)+k(t-(n+1)/2), t=1,2,...,n. Then the process Y(t) is not second-order stationary process since it is contaminated with linear trend, k – degree of contamination. Define R(h) – covariogram for Y(t) process and Define Rs(h) - covariogram for S(t) process. Could you help me to show that estimate of R(h) converges in probability to estimate of Rs(h) + ((k^2) * (n^2))/12 Thank in advance [/QUOTE]
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Covariogram estimation for the process contaminated with linear trend
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