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