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- Norman R. Draper

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
50
Citations
69,226
247
World Ranking
760
National Ranking
379

1971 - Fellow of the American Statistical Association (ASA)

- Statistics
- Algebra
- Geometry

His main research concerns Statistics, Regression analysis, Econometrics, Applied mathematics and Combinatorics. Statistics and Mathematical optimization are frequently intertwined in his study. In his study, Matrix representation and Mathematical proof is strongly linked to Linear regression, which falls under the umbrella field of Regression analysis.

His work carried out in the field of Econometrics brings together such families of science as Estimation and Regression. His Response surface methodology research incorporates themes from Transformation, Ridge, Lack-of-fit sum of squares and Least squares. His studies in Segmented regression integrate themes in fields like Regression dilution, Generalized linear model, Local regression and Factor regression model.

- Applied Regression Analysis (18298 citations)
- Empirical Model-Building and Response Surfaces (4589 citations)
- Applied regression analysis 2nd ed. (3054 citations)

Norman R. Draper mainly investigates Statistics, Applied mathematics, Econometrics, Regression analysis and Combinatorics. Norman R. Draper regularly links together related areas like Surface in his Statistics studies. His research in Applied mathematics intersects with topics in Mixture model and Mathematical optimization.

His Econometrics study incorporates themes from Outlier and Bayesian multivariate linear regression. His work deals with themes such as Linear regression and Bibliography, which intersect with Regression analysis. Norman R. Draper is conducting research in Total least squares and Least squares as part of his Lack-of-fit sum of squares study.

- Statistics (39.45%)
- Applied mathematics (19.53%)
- Econometrics (16.02%)

- Statistics (39.45%)
- Mathematical optimization (10.94%)
- Applied mathematics (19.53%)

His scientific interests lie mostly in Statistics, Mathematical optimization, Applied mathematics, Econometrics and Art history. His study involves Regression analysis, Regression, Autocorrelation, Durbin–Watson statistic and Total sum of squares, a branch of Statistics. While the research belongs to areas of Mathematical optimization, Norman R. Draper spends his time largely on the problem of Factorial experiment, intersecting his research to questions surrounding Design of experiments and Plackett–Burman design.

His Applied mathematics study combines topics from a wide range of disciplines, such as Explained sum of squares, Quadratic equation, Linear model, Transformation and Least squares. His study in Least squares is interdisciplinary in nature, drawing from both Coefficient of determination and Mathematical analysis. The Econometrics study combines topics in areas such as Polynomial regression and Local regression.

- Fitting a Straight Line by Least Squares (35 citations)
- Selecting the “Best” Regression Equation (22 citations)
- An Introduction to Nonlinear Estimation (12 citations)

- Statistics
- Algebra
- Geometry

Norman R. Draper mainly focuses on Statistics, Mathematical optimization, Applied mathematics, Least squares and Econometrics. A large part of his Statistics studies is devoted to Regression analysis. As a part of the same scientific family, he mostly works in the field of Mathematical optimization, focusing on Factorial experiment and, on occasion, Design of experiments, Engineering drawing and Equidistant.

The concepts of his Applied mathematics study are interwoven with issues in Quadratic equation, D optimality and Combinatorics, Composition. His study explores the link between Least squares and topics such as Explained sum of squares that cross with problems in Residual sum of squares and Method of steepest descent. His research on Econometrics also deals with topics like

- Polynomial regression and related Analysis of covariance, Variance function, Unit-weighted regression and Variance-based sensitivity analysis,
- Local regression and related One-way analysis of variance, Simple linear regression and Bayesian multivariate linear regression.

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.

Applied Regression Analysis

Norman Richard Draper;Harry Smith.

**(1966)**

35977 Citations

Empirical Model-Building and Response Surfaces

George E P Box;Norman R Draper.

**(1987)**

9518 Citations

Applied regression analysis

Norman R. Draper.

Applied regression analysis **(1998)**

5531 Citations

Applied regression analysis 2nd ed.

Draper Nr;Smith H.

Journal of the American Statistical Association **(1981)**

4979 Citations

Applied Regression Analysis: Draper/Applied Regression Analysis

Norman R. Draper;Harry Smith.

**(1998)**

4440 Citations

A Basis for the Selection of a Response Surface Design

G. E. P. Box;Norman R. Draper.

Journal of the American Statistical Association **(1959)**

937 Citations

Response Surfaces, Mixtures, and Ridge Analyses

George E. P. Box;Norman Richard Draper.

**(2007)**

547 Citations

D-Optimality for Regression Designs: A Review

R. C. St. John;N. R. Draper.

Technometrics **(1975)**

464 Citations

The Bayesian estimation of common parameters from several responses

George E. P. Box;Norman R. Draper.

Biometrika **(1965)**

365 Citations

Factorial Designs, the |X′X| Criterion, and Some Related Matters

M. J. Box;N. R. Draper.

Technometrics **(1971)**

283 Citations

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