Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process
Kybernetika (1978)
- Volume: 14, Issue: 3, page (206)-220
- ISSN: 0023-5954
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topŠtulajter, František. "Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process." Kybernetika 14.3 (1978): (206)-220. <http://eudml.org/doc/28566>.
@article{Štulajter1978,
author = {Štulajter, František},
journal = {Kybernetika},
language = {eng},
number = {3},
pages = {(206)-220},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process},
url = {http://eudml.org/doc/28566},
volume = {14},
year = {1978},
}
TY - JOUR
AU - Štulajter, František
TI - Nonlinear estimators of polynomials in mean values of a Gaussian stochastic process
JO - Kybernetika
PY - 1978
PB - Institute of Information Theory and Automation AS CR
VL - 14
IS - 3
SP - (206)
EP - 220
LA - eng
UR - http://eudml.org/doc/28566
ER -
References
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- D. L. Duttweiler T. Kailath, RKHS Approach to Detection and Estimation Problems - Part IV. Non Gaussian Detection, IEEE Trans. Inf. Th., IT-19 (1973), 19-28. (1973) MR0406673
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- G. Kallianpur, The Role of RKHS in the Study of Gaussian Processes, In Advances in Probability, vol. 2, M. Dekker INC. New York 1970, 59-83. (1970) MR0283866
- E. Parzen, Statistical Inference on Time Series by Hilbert Space Methods, Technical report No 23, Stanford 1959. (Reprinted in the book E. Parzen: Time Series Analysis Papers. Holden-Day, San Francisco 1967.) (1959)
- E. Parzen, Statistical Inference on Time Series by RKHS Methods II, Proc. 12th Biennial Canadian Math. Congress, R. Pyke (Ed.), Providence, R. I.: Amer. Math. Soc. 1969, 1 - 37. (1969) MR0275616
- A. Pázman, Plans d'expérience pour les estimations de fonctionnelles non-linéaires, Annales de l'Institut H. Poincaré 13 (1977), No 3. (1977) MR0455230
Citations in EuDML Documents
top- František Štulajter, Some nonlinear statistical problems of a Poisson process
- Júlia Volaufová, Estimation of polynomials in the regression model
- František Štulajter, Locally best unbiased estimates of functionals of covariance functions of a Gaussian stochastic process
- Czesław Stępniak, Quadratic unbiased estimation of nonstandard parametric functions
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