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- Herbert Robbins

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
43
Citations
29,879
110
World Ranking
1114
National Ranking
515

1975 - Fellow of John Simon Guggenheim Memorial Foundation

1974 - Member of the National Academy of Sciences

1969 - Wald Memorial Lecturer

1952 - Fellow of John Simon Guggenheim Memorial Foundation

1950 - Fellow of the American Association for the Advancement of Science (AAAS)

- Statistics
- Normal distribution
- Random variable

Herbert Robbins spends much of his time researching Statistics, Random variable, Combinatorics, Mathematical optimization and Distribution function. Herbert Robbins combines subjects such as Composition, Statistical theory and Quantities of information with his study of Random variable. The study incorporates disciplines such as Stirling engine, Stirling's approximation, Sequence and Algebra in addition to Combinatorics.

His work in Multivariate random variable addresses issues such as Marginal distribution, which are connected to fields such as Applied mathematics. His Minimax approximation algorithm study in the realm of Applied mathematics connects with subjects such as Stochastic approximation. His Constant research integrates issues from Expected value, Continuous-time stochastic process, Stochastic optimization and Monotonic function.

- A Stochastic Approximation Method (6007 citations)
- Some aspects of the sequential design of experiments (1678 citations)
- Asymptotically efficient adaptive allocation rules (1620 citations)

His primary scientific interests are in Statistics, Random variable, Combinatorics, Applied mathematics and Bayes' theorem. Herbert Robbins interconnects Discrete mathematics, Probability distribution, Sequence and Distribution function in the investigation of issues within Random variable. His Combinatorics study also includes

- Sequential decision which connect with Bayes test,
- Expected value most often made with reference to Joint probability distribution.

Mean squared error and Sequential estimation is closely connected to Estimator in his research, which is encompassed under the umbrella topic of Applied mathematics. Herbert Robbins has included themes like Mathematical economics, Prior probability, Mathematical optimization and Econometrics in his Bayes' theorem study. In the subject of general Mathematical optimization, his work in Optimal stopping is often linked to Mathematical finance, thereby combining diverse domains of study.

- Statistics (26.85%)
- Random variable (19.44%)
- Combinatorics (18.52%)

- Statistics (26.85%)
- Bayes' theorem (13.89%)
- Econometrics (12.96%)

His primary areas of study are Statistics, Bayes' theorem, Econometrics, Mathematical optimization and Applied mathematics. His biological study spans a wide range of topics, including Center and Constant. His work deals with themes such as Class and Sequential analysis, which intersect with Econometrics.

His Mathematical optimization study integrates concerns from other disciplines, such as Stopping time and Thompson sampling. His Applied mathematics research incorporates elements of M-estimator, Probability density function, Restricted maximum likelihood, Random variable and Poisson distribution. The Sampling study combines topics in areas such as Expected value, Estimator and Randomness.

- Asymptotically efficient adaptive allocation rules (1620 citations)
- What is mathematics : an elementary approach to ideas and methods (231 citations)
- Sequential Estimation of the Mean of a Normal Population (129 citations)

- Statistics
- Normal distribution
- Random variable

Herbert Robbins mostly deals with Statistics, Mathematical optimization, Bayes' theorem, Sampling and Applied mathematics. His work on Outcome, Binomial and Multinomial distribution as part of general Statistics research is often related to Negative multinomial distribution and Empirical probability, thus linking different fields of science. His Mathematical optimization research is multidisciplinary, incorporating elements of Stopping time and Thompson sampling.

His Bayes' theorem research is multidisciplinary, relying on both Prior probability, Null hypothesis, Econometrics and Random variable. His Sampling study incorporates themes from Sample, Sequential estimation, Estimator and Constant. His study of Applied mathematics brings together topics like Stochastic approximation and Set.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

A Stochastic Approximation Method

Herbert Robbins;Sutton Monro.

Annals of Mathematical Statistics **(1951)**

11614 Citations

Asymptotically efficient adaptive allocation rules

T.L Lai;Herbert Robbins.

Advances in Applied Mathematics **(1985)**

3031 Citations

Some aspects of the sequential design of experiments

Herbert Robbins.

Bulletin of the American Mathematical Society **(1952)**

2905 Citations

An Empirical Bayes Approach to Statistics

Herbert E. Robbins.

Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Contributions to the Theory of Statistics **(1956)**

1301 Citations

Complete Convergence and the Law of Large Numbers

P. L. Hsu;Herbert Robbins.

Proceedings of the National Academy of Sciences of the United States of America **(1947)**

1185 Citations

Great expectations: The theory of optimal stopping

Yuan Shih Chow;Herbert Ellis Robbins;David Siegmund.

**(1971)**

1158 Citations

What Is Mathematics

Richard Courant;Herbert Robbins.

**(1941)**

1036 Citations

A Remark on Stirling’s Formula

Herbert Robbins.

American Mathematical Monthly **(1955)**

956 Citations

The Empirical Bayes Approach to Statistical Decision Problems

Herbert Robbins.

Annals of Mathematical Statistics **(1964)**

839 Citations

The Central Limit Theorem for Dependent Random Variables

Wassily Hoeffding;Herbert Robbins.

Duke Mathematical Journal **(1948)**

642 Citations

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