{"status":"public","date_updated":"2024-04-24T12:48:54Z","date_created":"2023-01-30T11:12:55Z","extern":"1","page":"373–378","publication":"Orthogonal polynomials and their applications (Erice, 1990)","_id":"40656","citation":{"ama":"Rösler M. On optimal linear mean estimators for weakly stationary stochastic processes. In: <i>Orthogonal Polynomials and Their Applications (Erice, 1990)</i>. IMACS Ann. Comput. Appl. Math., 9,; 1991:373–378.","short":"M. Rösler, in: Orthogonal Polynomials and Their Applications (Erice, 1990), IMACS Ann. Comput. Appl. Math., 9, 1991, pp. 373–378.","apa":"Rösler, M. (1991). On optimal linear mean estimators for weakly stationary stochastic processes. <i>Orthogonal Polynomials and Their Applications (Erice, 1990)</i>, 373–378.","chicago":"Rösler, Margit. “On Optimal Linear Mean Estimators for Weakly Stationary Stochastic Processes.” In <i>Orthogonal Polynomials and Their Applications (Erice, 1990)</i>, 373–378. IMACS Ann. Comput. Appl. Math., 9, 1991.","ieee":"M. Rösler, “On optimal linear mean estimators for weakly stationary stochastic processes,” in <i>Orthogonal polynomials and their applications (Erice, 1990)</i>, 1991, pp. 373–378.","mla":"Rösler, Margit. “On Optimal Linear Mean Estimators for Weakly Stationary Stochastic Processes.” <i>Orthogonal Polynomials and Their Applications (Erice, 1990)</i>, IMACS Ann. Comput. Appl. Math., 9, 1991, pp. 373–378.","bibtex":"@inproceedings{Rösler_1991, title={On optimal linear mean estimators for weakly stationary stochastic processes}, booktitle={Orthogonal polynomials and their applications (Erice, 1990)}, publisher={IMACS Ann. Comput. Appl. Math., 9,}, author={Rösler, Margit}, year={1991}, pages={373–378} }"},"author":[{"id":"37390","first_name":"Margit","last_name":"Rösler","full_name":"Rösler, Margit"}],"publication_status":"published","user_id":"93826","publisher":"IMACS Ann. Comput. Appl. Math., 9,","language":[{"iso":"eng"}],"type":"conference","department":[{"_id":"555"}],"year":"1991","title":"On optimal linear mean estimators for weakly stationary stochastic processes"}