What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Probability distribution
Heleno Bolfarine mainly investigates Statistics, Applied mathematics, Skew normal distribution, Kurtosis and Generalized normal distribution.
Statistics is frequently linked to Econometrics in his study.
His research in Applied mathematics tackles topics such as Expectation–maximization algorithm which are related to areas like Marginal likelihood and Mixed model.
His study looks at the relationship between Skew normal distribution and topics such as Prior probability, which overlap with Probit model, Parametric statistics, Sample size determination and Bayes estimator.
His Kurtosis study integrates concerns from other disciplines, such as Heavy-tailed distribution, Distribution, Inference, Compound probability distribution and Generalized function.
His Generalized normal distribution research is multidisciplinary, incorporating elements of Inverse distribution and Variance-gamma distribution.
His most cited work include:
- Skew-normal Linear Mixed Models (148 citations)
- Skew-symmetric distributions generated by the distribution function of the normal distribution (93 citations)
- Prediction Theory for Finite Populations (93 citations)
What are the main themes of his work throughout his whole career to date?
Heleno Bolfarine focuses on Statistics, Applied mathematics, Regression analysis, Econometrics and Bayesian probability.
His Estimator, Normal distribution, Errors-in-variables models, Asymptotic distribution and Prior probability study are his primary interests in Statistics.
His study in Applied mathematics is interdisciplinary in nature, drawing from both Skew normal distribution, Expectation–maximization algorithm, Mathematical optimization, Fisher information and Kurtosis.
Heleno Bolfarine has included themes like Generalized normal distribution and Algorithm in his Skew normal distribution study.
His studies deal with areas such as Null, Multivariate statistics, Linear regression and Regression as well as Regression analysis.
His work carried out in the field of Econometrics brings together such families of science as Bayesian linear regression and Gibbs sampling.
He most often published in these fields:
- Statistics (62.90%)
- Applied mathematics (32.58%)
- Regression analysis (17.19%)
What were the highlights of his more recent work (between 2017-2021)?
- Applied mathematics (32.58%)
- Maximum likelihood (7.24%)
- Statistics (62.90%)
In recent papers he was focusing on the following fields of study:
Heleno Bolfarine mostly deals with Applied mathematics, Maximum likelihood, Statistics, Kurtosis and Expectation–maximization algorithm.
His Applied mathematics research includes elements of Distribution, Fisher information, Inference, Normal distribution and Generalization.
His Maximum likelihood research incorporates themes from Algorithm and Distribution.
Heleno Bolfarine combines topics linked to Bounded function with his work on Statistics.
The study incorporates disciplines such as Estimator and Exponential distribution in addition to Kurtosis.
The various areas that Heleno Bolfarine examines in his Expectation–maximization algorithm study include Skew normal distribution, Generalized linear mixed model and Rayleigh distribution.
Between 2017 and 2021, his most popular works were:
- Bimodal symmetric-asymmetric power-normal families (15 citations)
- Gumbel distribution with heavy tails and applications to environmental data (13 citations)
- Bimodality based on the generalized skew-normal distribution (5 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Probability distribution
His primary areas of study are Applied mathematics, Kurtosis, Normal distribution, Maximum likelihood and Half-normal distribution.
His research in Applied mathematics intersects with topics in Pearson distribution, Statistics and Asymptotic distribution, Ratio distribution.
His Kurtosis study combines topics in areas such as Skew normal distribution, Estimator, Fisher information and Gumbel distribution.
His studies in Skew normal distribution integrate themes in fields like Calculus and Combinatorics.
Heleno Bolfarine interconnects Zero, Probabilistic logic, Inference and Truncation in the investigation of issues within Maximum likelihood.
His Half-normal distribution study combines topics from a wide range of disciplines, such as Entropy and Special case.
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.
