Estimation in white Gaussian noise by means of finite number of linear statistics
Teoriâ veroâtnostej i ee primeneniâ, Tome 25 (1980) no. 2, pp. 278-290

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We consider the asymptotical properties of estimators $T$, which are measurable in respect to statistics $$ Y_i=\int_0^1 \psi_i(t)\,dX_\varepsilon(t) $$ if the observed process $X_\varepsilon(t)$ is determined by (1). The problem is to find the best «filters» $\psi_1(t),\dots,\psi_N(t)$ for subsequent estimation of $\theta$. It is proved that the best in minimax sense are the functions $\psi_i$ which determine the $N$-dimensional projector on the subspace, which is the tightest one to $\partial S/\partial\theta$ in some sense. More precisely it is necessary to consider the tightest projector among the admissible (in the sense of (11)) projectors. The examples, for which the optimal filters $\psi_i$ can be found, are considered.
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     author = {G. K. Golubev and R. Z. Has'minskiǐ},
     title = {Estimation in white {Gaussian} noise by means of finite number of linear statistics},
     journal = {Teori\^a vero\^atnostej i ee primeneni\^a},
     pages = {278--290},
     publisher = {mathdoc},
     volume = {25},
     number = {2},
     year = {1980},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TVP_1980_25_2_a3/}
}
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G. K. Golubev; R. Z. Has'minskiǐ. Estimation in white Gaussian noise by means of finite number of linear statistics. Teoriâ veroâtnostej i ee primeneniâ, Tome 25 (1980) no. 2, pp. 278-290. http://geodesic.mathdoc.fr/item/TVP_1980_25_2_a3/