What is he best known for?
The fields of study he is best known for:
- Statistics
- Optics
- Regression analysis
Bruce R. Kowalski focuses on Statistics, Partial least squares regression, Calibration, Analytical chemistry and Multivariate statistics.
His work in the fields of Statistics, such as Multivariate calibration, overlaps with other areas such as Biological system and Rank.
His Multivariate calibration research incorporates elements of Orthogonal signal correction and Reliability engineering.
His research in Partial least squares regression intersects with topics in Latent variable, Regression analysis, Polynomial regression, Fortran and Algorithm.
His Calibration research includes elements of Linear model, Chemometrics, Sampling, Least squares and Autocorrelation.
His research in the fields of Internal standard, Matrix, Analyte and Mass spectrometry overlaps with other disciplines such as Low resolution.
His most cited work include:
- Partial least-squares regression: a tutorial (5099 citations)
- Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution (761 citations)
- An introduction to multivariate calibration and analysis (473 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Analytical chemistry, Statistics, Calibration, Artificial intelligence and Partial least squares regression.
He has researched Analytical chemistry in several fields, including Chromatography, Calibration and Detector.
Within one scientific family, Bruce R. Kowalski focuses on topics pertaining to Algorithm under Statistics, and may sometimes address concerns connected to Data processing.
The study incorporates disciplines such as Multivariate analysis, Regression, Chemometrics, Applied mathematics and Multivariate calibration in addition to Calibration.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.
Bruce R. Kowalski has researched Partial least squares regression in several fields, including Regression analysis and Principal component regression.
He most often published in these fields:
- Analytical chemistry (26.88%)
- Statistics (25.63%)
- Calibration (20.63%)
What were the highlights of his more recent work (between 1993-2006)?
- Statistics (25.63%)
- Calibration (20.63%)
- Analytical chemistry (26.88%)
In recent papers he was focusing on the following fields of study:
Statistics, Calibration, Analytical chemistry, Algorithm and Chemometrics are his primary areas of study.
His work in the fields of Statistics, such as Partial least squares regression and Principal component analysis, intersects with other areas such as Rank and Term.
The concepts of his Calibration study are interwoven with issues in Figure of merit, Multivariate statistics, Applied mathematics and Local regression.
His Analytical chemistry study integrates concerns from other disciplines, such as Singular value decomposition and Fluorescence.
His Algorithm research incorporates elements of Weighting, Background noise, Data processing and Sensitivity.
His studies in Chemometrics integrate themes in fields like Statistician, Management science and Spectrum analyzer.
Between 1993 and 2006, his most popular works were:
- Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution (761 citations)
- Theory of analytical chemistry (445 citations)
- Net analyte signal calculation in multivariate calibration (303 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Optics
- Machine learning
His primary scientific interests are in Calibration, Statistics, Chemometrics, Analytical chemistry and Rank.
While the research belongs to areas of Calibration, he spends his time largely on the problem of Figure of merit, intersecting his research to questions surrounding Sensitivity and Calculus.
In most of his Statistics studies, his work intersects topics such as Algorithm.
He combines subjects such as Statistician and Management science with his study of Chemometrics.
His Analyte study in the realm of Analytical chemistry connects with subjects such as Gram and Component.
The Partial least squares regression study combines topics in areas such as Polynomial regression, Segmented regression, Robust regression, Regression analysis and Regression diagnostic.
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