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

Voir la notice de l'article provenant de la source eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts

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 
@article{PIM_2001_N_S_70_84_a7,
     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},
     pages = {63 },
     publisher = {mathdoc},
     volume = {_N_S_70},
     number = {84},
     year = {2001},
     zbl = {1034.62087},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/PIM_2001_N_S_70_84_a7/}
}
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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/