What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Artificial intelligence
Narayanaswamy Balakrishnan mainly focuses on Statistics, Order statistic, Applied mathematics, Estimator and Exponential distribution.
Statistics and Inference are frequently intertwined in his study.
The study incorporates disciplines such as Recurrence relation, Combinatorics, Distribution, Algorithm and Censoring in addition to Order statistic.
His study on Applied mathematics also encompasses disciplines like
- Mathematical optimization that connect with fields like Weibull distribution,
- Censoring together with Maximum likelihood and Competing risks.
His work deals with themes such as Mean squared error and Interval estimation, which intersect with Estimator.
His work carried out in the field of Exponential distribution brings together such families of science as Conditional probability distribution, Random variable and Exponential function.
His most cited work include:
- Continuous univariate distributions (7057 citations)
- A first course in order statistics (1421 citations)
- Continuous Multivariate Distributions (804 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Statistics, Applied mathematics, Order statistic, Estimator and Exponential distribution.
His research in Statistics intersects with topics in Econometrics and Exponential function.
His Applied mathematics research integrates issues from Inference, Distribution, Mathematical optimization and Censoring.
His study in Order statistic is interdisciplinary in nature, drawing from both Recurrence relation, Combinatorics, Random variable and Sample.
His Estimator study frequently draws connections to other fields, such as Estimation theory.
His research combines Censoring and Exponential distribution.
He most often published in these fields:
- Statistics (52.70%)
- Applied mathematics (25.36%)
- Order statistic (24.57%)
What were the highlights of his more recent work (between 2015-2021)?
- Statistics (52.70%)
- Applied mathematics (25.36%)
- Order statistic (24.57%)
In recent papers he was focusing on the following fields of study:
Narayanaswamy Balakrishnan mainly focuses on Statistics, Applied mathematics, Order statistic, Estimator and Monte Carlo method.
His Statistics research incorporates themes from Inference and Econometrics.
Narayanaswamy Balakrishnan interconnects Probability distribution, Distribution, Maximum likelihood, Exponential distribution and Exponential function in the investigation of issues within Applied mathematics.
He has researched Order statistic in several fields, including Random variable and Combinatorics.
Estimator is closely attributed to One shot in his work.
In his study, which falls under the umbrella issue of Expectation–maximization algorithm, Algorithm is strongly linked to Weibull distribution.
Between 2015 and 2021, his most popular works were:
- The Art of Progressive Censoring: Applications to Reliability and Quality (85 citations)
- Birnbaum‐Saunders distribution: A review of models, analysis, and applications (37 citations)
- Expectation maximization-based likelihood inference for flexible cure rate models with Weibull lifetimes (36 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Artificial intelligence
His primary areas of investigation include Statistics, Applied mathematics, Weibull distribution, Order statistic and Expectation–maximization algorithm.
His Statistics research is multidisciplinary, incorporating perspectives in Control chart and Econometrics.
His study looks at the relationship between Applied mathematics and fields such as Exponential distribution, as well as how they intersect with chemical problems.
His work in Weibull distribution addresses issues such as Series, which are connected to fields such as Parallel computing, Stochastic ordering and Birnbaum–Saunders distribution.
He has included themes like Exponentiated Weibull distribution, Random variable, Independent and identically distributed random variables and Majorization, Combinatorics in his Order statistic study.
His Expectation–maximization algorithm study combines topics in areas such as Poisson distribution, Inference, Monte Carlo method and Mathematical optimization.
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