Summary
The statistician of the 21st century will have been educated in a modern computing environment and will expect statistical modelling software to reflect recent advances in computer technology. Existing statistical software and the current languages used for statistical analysis are based on somewhat old-fashioned computing concepts. This paper discusses how modern computing languages might influence the design of a language for statistical analysis. A prototype package has been written which emulates GLIM, and with a GLIM related syntax, but within a functional programming environment. A brief account is given of functional programming concepts. The prototype language used (Standard ML) is discussed and some of its strengths and weaknesses outlined. Some ideas are presented on how this approach might be modified to give a modern computing environment for a statistical modelling package of the future.
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© 1989 Springer-Verlag Berlin Heidelberg
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Clarke, M., Gilchrist, R., Scallan, A., Slater, M. (1989). Functional programming for GLMs. In: Decarli, A., Francis, B.J., Gilchrist, R., Seeber, G.U.H. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 57. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3680-1_2
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DOI: https://doi.org/10.1007/978-1-4612-3680-1_2
Publisher Name: Springer, New York, NY
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