Article PDF
Avoid common mistakes on your manuscript.
References
Anscombe, F.: Large-sample theory of sequential estimation. Proc. Cambridge Philos. Soc. 48, 600–607 (1952).
Blum, J.: Approximation methods which converge with probability one. Ann. Math. Statistics 25, 382–386 (1954).
Burkholder, D.: On a class of stochastic approximation processes. Ann. Math. Statistics 27, 1044–1059 (1956).
CsŐrgŐ, M.: On the strong law of large numbers and the central limit theorem for martingales. Trans. Amer. Math. Soc. 131, 259–275 (1968).
Loginov, N.: Survey: methods of stochastic approximation. Automat. Remote Control 27, 707–728 (1966).
Robbins, H., Monro, S.: A stochastic approximation method. Ann. Math. Statistics 22, 400–407 (1951).
Sacks, J.: Asymptotic distribution of stochastic approximation procedures. Ann. Math. Statistics 29, 373–405 (1958).
Sielken, R.L., Jr.: Sequentially Determined Bounded Length Confidence Intervals for Stochastic Approximation Procedures of the Robbins-Monro Type. Ph. D. dissertation, Florida State University (1971).
Venter, J.: An extension of the Robbins-Monro procedure. Ann. Math. Statistics 38, 181–190 (1967).
Wasan, M.: Stochastic Approximation, New York: Cambridge University Press (1969).
Author information
Authors and Affiliations
Additional information
This paper is part of the author's doctoral dissertation which was supported in part by the Office of Naval Research and the National Institute of General Medical Sciences.
Rights and permissions
About this article
Cite this article
Sielken, R.L. Stopping times for stochastic approximation procedures. Z. Wahrscheinlichkeitstheorie verw Gebiete 26, 67–75 (1973). https://doi.org/10.1007/BF00533961
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF00533961