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John Nelder

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Through Design of experiments, High-level programming language and Linear regression

Contributions

Nelder's work was influential in statistics. While leading research at Rothamsted Experimental Station, Nelder developed and supervised the updating of the statistical software packages GLIM and GenStat: Both packages are flexible high-level programming languages that allow statisticians to formulate linear models concisely. GLIM influenced later environments for statistical computing such as S-PLUS and R. Both GLIM and GenStat have powerful facilities for the analysis of variance for block experiments, an area where Nelder made many contributions.

In statistical theory, Nelder proposed the generalized linear model together with Robert Wedderburn. Nelder and Wedderburn formulated generalized linear models as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression. They proposed an iteratively reweighted least squares method for maximum likelihood estimation of the model parameters.

In statistical inference, Nelder (along with George Barnard and A. W. F. Edwards) emphasized the importance of the likelihood in data analysis, promoting this "likelihood approach" as an alternative to frequentist and Bayesian statistics.

In response-surface optimization, Nelder and Roger Mead proposed the Nelder–Mead simplex heuristic, widely used in engineering and statistics.

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