Estimating of Parameters: Nuar(1) Process
Publications de l'Institut Mathématique, _N_S_70 (2001) no. 84, p. 63 .

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We applied the method of conditional least squares for estimating parameters of NUAR(1). This process can be represented as the random coefficient autoregressive time series of the form $ X_n=U_n X_{n-1}+V_n, $ where $\{(U_n,V_n)\}$ is the sequence of independent identically distributed random vectors such that supply the elements of the sequence $\{X_n\}$ with $\mathcal{U}(0,1)$ marginal distribution. Defined estimates were the functions of the estimates of moments $E(U_n)$ and $E(U_n V_n)$ and they are strong consistent and asymptotically normally distributed.
Classification : 62M10
Keywords: conditional least squares estimation, uniform autoregressive process, asymptotic normality, strong consistency
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     author = {Miroslav M. Risti\'c and Biljana \v{C}. Popovi\'c},
     title = {Estimating of {Parameters:} {Nuar(1)} {Process}},
     journal = {Publications de l'Institut Math\'ematique},
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     publisher = {mathdoc},
     volume = {_N_S_70},
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     year = {2001},
     zbl = {1034.62087},
     language = {en},
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Miroslav M. Ristić; Biljana Č. Popović. Estimating of Parameters: Nuar(1) Process. Publications de l'Institut Mathématique, _N_S_70 (2001) no. 84, p. 63 . http://geodesic.mathdoc.fr/item/PIM_2001_N_S_70_84_a7/