What is he best known for?
The fields of study he is best known for:
- Statistics
- Law
- Normal distribution
Joseph B. Kadane mostly deals with Mathematical optimization, Econometrics, Bayesian probability, Applied mathematics and Prior probability.
The study incorporates disciplines such as Exponential family, Bayesian linear regression, Bayesian inference, Search theory and Conjugate prior in addition to Mathematical optimization.
He has included themes like Mathematical economics, Bayesian statistics, Variables, Joint probability distribution and Decision theory in his Econometrics study.
Joseph B. Kadane regularly links together related areas like Data mining in his Bayesian probability studies.
He has researched Applied mathematics in several fields, including Statistics, Mode, Marginal distribution, Laplace's method and Conway–Maxwell–Poisson distribution.
His research in Laplace's method tackles topics such as Marginal likelihood which are related to areas like Bayes factor.
His most cited work include:
- Accurate Approximations for Posterior Moments and Marginal Densities (1595 citations)
- Statistical Methods for Eliciting Probability Distributions (587 citations)
- An overview of robust Bayesian analysis (432 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Bayesian probability, Econometrics, Statistics, Mathematical economics and Mathematical optimization.
His Bayesian probability study is concerned with the field of Artificial intelligence as a whole.
Many of his studies involve connections with topics such as Bayesian statistics and Econometrics.
His research on Statistics frequently links to adjacent areas such as Census.
The various areas that he examines in his Mathematical economics study include Philosophy of science and Foundations of statistics.
He most often published in these fields:
- Bayesian probability (18.06%)
- Econometrics (17.02%)
- Statistics (13.35%)
What were the highlights of his more recent work (between 2009-2021)?
- Combinatorics (7.33%)
- Econometrics (17.02%)
- Bayesian probability (18.06%)
In recent papers he was focusing on the following fields of study:
Combinatorics, Econometrics, Bayesian probability, Discrete mathematics and Statistics are his primary areas of study.
His Combinatorics study integrates concerns from other disciplines, such as Uniform distribution and Frequency.
Many of his studies on Econometrics apply to Dominance as well.
His study on Bayesian probability is covered under Artificial intelligence.
Joseph B. Kadane focuses mostly in the field of Discrete mathematics, narrowing it down to topics relating to Coherence and, in certain cases, Sigma additivity and Scoring rule.
He works on Statistics which deals in particular with Bayesian inference.
Between 2009 and 2021, his most popular works were:
- Coherent choice functions under uncertainty (66 citations)
- Simultaneous Linear Quantile Regression: A Semiparametric Bayesian Approach (66 citations)
- Principles of Uncertainty (36 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Law
- Normal distribution
Joseph B. Kadane mainly focuses on Econometrics, Bayesian probability, Coherence, Environmental science and Fingerprint.
Joseph B. Kadane performs multidisciplinary studies into Econometrics and Calibration curve in his work.
His Bayesian probability research is included under the broader classification of Artificial intelligence.
His Coherence research integrates issues from Brier score, Scoring rule, Choice function, Axiom and Decision problem.
Joseph B. Kadane combines subjects such as Dominance, Simple, Lexicographical order, Generalization and Decision rule with his study of Scoring rule.
His Fingerprint research includes elements of Certainty, Item response theory, Information retrieval and Natural language processing.
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