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- Richard D. Gill

Mathematics

Netherlands

2023

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
53
Citations
15,863
183
World Ranking
644
National Ranking
1

2023 - Research.com Mathematics in Netherlands Leader Award

2022 - Research.com Mathematics in Netherlands Leader Award

1999 - Royal Netherlands Academy of Arts and Sciences

- Statistics
- Quantum mechanics
- Algebra

His scientific interests lie mostly in Estimator, Econometrics, Applied mathematics, Mathematical optimization and Statistics. His research in the fields of Survival function overlaps with other disciplines such as Gaussian process. Richard D. Gill has included themes like Martingale, Statistical hypothesis testing, Missing data, Joint probability distribution and Survival data in his Econometrics study.

His Martingale research incorporates elements of Multivariate statistics and Regression dilution. His study in Proportional hazards model, Covariate, Regression analysis and Counting process is carried out as part of his studies in Statistics. The various areas that he examines in his Counting process study include Nelson–Aalen estimator, Data mining and Left truncation.

- Cox's Regression Model for Counting Processes: A Large Sample Study (3117 citations)
- Statistical Models Based on Counting Processes. (2513 citations)
- Censoring and stochastic integrals (482 citations)

Richard D. Gill mostly deals with Statistics, Statistical physics, Applied mathematics, Mathematical economics and Econometrics. His research related to Expectation–maximization algorithm and Proportional hazards model might be considered part of Statistics. His work carried out in the field of Statistical physics brings together such families of science as Quantum system, Quantum entanglement, State, Quantum information and Quantum statistical mechanics.

His Applied mathematics research is multidisciplinary, incorporating perspectives in Estimator, Pointwise, Mathematical optimization and Conditional probability distribution. Richard D. Gill has researched Mathematical economics in several fields, including Argument and Bell's theorem. His study in Econometrics is interdisciplinary in nature, drawing from both Regression analysis, Markov process, Survival data and Statistical hypothesis testing.

- Statistics (15.62%)
- Statistical physics (12.89%)
- Applied mathematics (12.89%)

- Bell's theorem (7.81%)
- Hidden variable theory (7.03%)
- Simple (6.25%)

Richard D. Gill spends much of his time researching Bell's theorem, Hidden variable theory, Simple, Quantum and Mathematical economics. His Bell's theorem research integrates issues from Quantum nonlocality and Counterexample. In his study, which falls under the umbrella issue of Quantum, Statistical physics is strongly linked to Trigonometric functions.

His Mathematical economics study incorporates themes from Judgement, Argument, Contradiction and Bayesian inference. His work investigates the relationship between Causality and topics such as No-communication theorem that intersect with problems in Statistics. His work blends Statistics and Forensic statistics studies together.

- On asymptotic quantum statistical inference (49 citations)
- Statistics, causality and Bell's theorem (43 citations)
- Quantum local asymptotic normality based on a new quantum likelihood ratio (42 citations)

- Statistics
- Quantum mechanics
- Mathematical analysis

Richard D. Gill mainly investigates Bell's theorem, Applied mathematics, Quantum, Mathematical economics and Normalization. His Bell's theorem study combines topics from a wide range of disciplines, such as Causality, Quantum nonlocality and Statistical physics. Richard D. Gill has researched Applied mathematics in several fields, including Estimator, Strong consistency, Bounded function and Probability mass function.

The Quantum study which covers Local asymptotic normality that intersects with Domain, Statistical model, Smoothness, State and Statistical inference. His research in Normalization tackles topics such as Discrete mathematics which are related to areas like Calculus. His Calculus research is multidisciplinary, relying on both No-communication theorem, Mistake, Algebraic error and Statistics.

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.

Cox's Regression Model for Counting Processes: A Large Sample Study

Per Kragh Andersen;Richard D. Gill.

Annals of Statistics **(1982)**

5063 Citations

Cox's Regression Model for Counting Processes: A Large Sample Study

Per Kragh Andersen;Richard D. Gill.

Annals of Statistics **(1982)**

5063 Citations

Statistical Models Based on Counting Processes.

Frank Coolen;P. K. Andersen;O. Borgan;R. D. Gill.

The Statistician **(1996)**

3946 Citations

Censoring and stochastic integrals

Richard D. Gill.

**(1980)**

1085 Citations

Censoring and stochastic integrals

Richard D. Gill.

**(1980)**

1085 Citations

A counting process approach to maximum likelihood estimation in frailty models

G. G. Nielsen;R. D. Gill;P. K. Andersen;T. I. A. Sørensen.

Scandinavian Journal of Statistics **(1992)**

800 Citations

A counting process approach to maximum likelihood estimation in frailty models

G. G. Nielsen;R. D. Gill;P. K. Andersen;T. I. A. Sørensen.

Scandinavian Journal of Statistics **(1992)**

800 Citations

A Survey of Product-Integration with a View Toward Application in Survival Analysis

Richard D. Gill;Soren Johansen.

Annals of Statistics **(1990)**

559 Citations

A Survey of Product-Integration with a View Toward Application in Survival Analysis

Richard D. Gill;Soren Johansen.

Annals of Statistics **(1990)**

559 Citations

Large Sample Behaviour of the Product-Limit Estimator on the Whole Line

Richard Gill.

Annals of Statistics **(1983)**

555 Citations

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