What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Mathematical analysis
Elias Masry focuses on Applied mathematics, Statistics, Asymptotic distribution, Estimator and Conditional expectation.
His research in Applied mathematics intersects with topics in Stochastic process and Mathematical optimization.
His work on Regression, Multivariate statistics, Strong consistency and Sampling scheme as part of general Statistics research is frequently linked to Alias, bridging the gap between disciplines.
His work deals with themes such as Series and Econometrics, which intersect with Asymptotic distribution.
His work in Estimator addresses issues such as Estimation theory, which are connected to fields such as Sequence, Legendre polynomials and Dimension.
His Conditional expectation research is multidisciplinary, incorporating elements of Function, Conditional probability distribution and Polynomial regression.
His most cited work include:
- MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES (371 citations)
- Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality (228 citations)
- Local Polynomial Estimation of Regression Functions for Mixing Processes (163 citations)
What are the main themes of his work throughout his whole career to date?
Statistics, Applied mathematics, Asymptotic distribution, Stochastic process and Mathematical analysis are his primary areas of study.
His research is interdisciplinary, bridging the disciplines of Rate of convergence and Statistics.
His Applied mathematics research includes themes of Strong consistency, Polynomial regression, Mathematical optimization, Convergence of random variables and Series.
His work carried out in the field of Polynomial regression brings together such families of science as Conditional probability distribution and Conditional expectation.
His Asymptotic distribution study combines topics from a wide range of disciplines, such as Nonparametric statistics, Polynomial, Covariance matrix, Nonlinear system and Signal.
His Stochastic process research incorporates elements of Discrete mathematics, Monte Carlo method and Constant.
He most often published in these fields:
- Statistics (38.89%)
- Applied mathematics (33.33%)
- Asymptotic distribution (23.15%)
What were the highlights of his more recent work (between 2005-2015)?
- Communication channel (12.04%)
- Statistics (38.89%)
- Electronic engineering (12.04%)
In recent papers he was focusing on the following fields of study:
Elias Masry mainly investigates Communication channel, Statistics, Electronic engineering, Fading and Asymptotic distribution.
Elias Masry interconnects Spread spectrum and Code division multiple access in the investigation of issues within Communication channel.
His research investigates the connection between Statistics and topics such as Algorithm that intersect with problems in Central limit theorem.
His Electronic engineering research includes elements of Multiple antenna, Interference, Telecommunications, Bit error rate and Radio receiver.
Elias Masry has included themes like Covariance matrix, Stationary process, Applied mathematics and Mixing in his Asymptotic distribution study.
The Applied mathematics study combines topics in areas such as Stochastic process, Fourier transform, Convergence of random variables and Nonuniform sampling.
Between 2005 and 2015, his most popular works were:
- Multivariate Signal Parameter Estimation Under Dependent Noise From 1-Bit Dithered Quantized Data (40 citations)
- A Digital Requantizer With Shaped Requantization Noise That Remains Well Behaved After Nonlinear Distortion (34 citations)
- Random sampling of deterministic signals: statistical analysis of Fourier transform estimates (34 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical analysis
- Normal distribution
His primary scientific interests are in Statistics, Asymptotic distribution, Algorithm, Stochastic process and Monte Carlo method.
His Noise research extends to Statistics, which is thematically connected.
His Asymptotic distribution research is multidisciplinary, relying on both Autoregressive–moving-average model, Nonuniform sampling, Estimation theory, Fourier transform and Applied mathematics.
The concepts of his Algorithm study are interwoven with issues in Spurious relationship, Oversampling and Nonlinear system.
The various areas that he examines in his Stochastic process study include Covariance matrix, Central limit theorem, Stratified sampling and Estimator.
His biological study spans a wide range of topics, including Rate of convergence, Fourier analysis and Convergence of random variables.
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.
