If you prefer you can read this as a pdf. At VSN International, we recognise that your analyses depend on the accuracy and validity of our software. We therefore take great care to check that the results that we produce are reliable and correct. This document summarizes some of the methods that we use to achieve this.
We use algorithms that are designed to give numerical accuracy and stability. These are mainly produced in-house by our team of well-trained developers. We also make use of the renowned and carefully-validated algorithms produced by the Numerical Algorithms Group (one of our shareholders).
We check the GenStat directives using an extensive suite of test programs whose results have been checked by
Procedures in the GenStat Procedure Library are assessed by an Editorial Board, who use similar methods to check that accepted procedures are useful, reliable and accompanied by clear documentation.
We recognise the crucial safety-net that timely, well-informed and helpful support can provide for our supported users.
Our technical development team includes statisticians with considerable experience of statistical consulting and teaching. We are thus very aware of the issues that can arise when statistical software is used by people with limited statistical experience or training. The menus, interfaced and algorithms in GenStat are designed to help these users to use statistics effectively and correctly. For example
VSNi was formed in 2001 as a spin-off company from Rothamsted Research and the Numerical Algorithms Group. This brought together the GenStat development group from Rothamsted with the statistical commercialisation group from NAG to provide a stronger collaboration of research and development with sales and marketing. This has enabled the development group to focus more closely on user needs while retaining their close links with the research community. So we believe that we are responsive to both user needs and research opportunities.
Rothamsted is probably the oldest agricultural research institute in the world, and is now recognised as a centre of excellence for science in support of sustainable land management and its environmental impact. Its scientific research ranges from studies of genetics, biochemistry, cell biology and soil processes to investigations at the ecosystem and landscape scale. Its interests in statistics began in 1919, when R.A. Fisher was appointed as its original statistician to study the accumulated results of the Rothamsted classical field experiments, which began in 1843 with the Broadbalk experiment on winter wheat. Fisher realised the need for improved statistical methods, and, over the next few years, laid the foundations of modern applied statistics. In fact, many of the standard methods that we now take for granted were originally devised by Fisher. Examples include analysis of variance, design of experiments, exact tests, discriminant analysis and maximum likelihood. Rothamsted became a pioneer of the use of computers in statistical analysis in 1954 when Frank Yates, Fisher’s successor as Head of Statistics at Rothamsted, obtained an Elliot 401 computer – one of the first computers to be used away from its manufacturing base. GenStat was the natural successor of this early work. Its development began at Rothamsted when John Nelder was appointed as the next Head of Statistics at Rothamsted, in 1968. Roger Payne took over its leadership in 1985, when John Nelder retired from Rothamsted, and continues in that role as VSNi’s Chief Science and Technology Officer. GenStat has benefited from the close relationship between statistical computing and statistical research and consulting at Rothamsted, and this relationship continues through the continuing links between VSNi and Rothamsted, where several of our technical staff have visiting positions. Other statistical theory and methods in GenStat that were originally developed by Rothamsted statisticians include generalized linear models (John Nelder), general balance (John Nelder originally, with further developments by Roger Payne), canonical variates analysis (John Gower) and REML analysis of mixed models (Robin Thompson). GenStat thus has a long history as the means of making available new statistical research that has been developed to address real biological research issues. We believe that this has given us unique insights into the needs of statisticians and scientists in biological research. The Numerical Algorithms Group (NAG) is one of the pioneers of mathematical, statistical, data mining and visualisation software. The services offered by NAG have been used by academic, government and industrial institutions globally for over 30 years. In 1971 NAG developed the first mathematical software library, which has evolved over the years and become the largest commercially available library of mathematical and statistical algorithms. We benefit from the expertise of our shareholders through their representatives on the VSNi Board. They augment our scientific expertise and provide valuable advice and direction on our activities.
We recognise the importance of keeping you up-to-date with new developments in statistics and computing. We thus have a regular schedule of new releases. GenStat itself has for many years followed an annual release schedule. Its new Editions generally include not only new statistical methodology but also enhanced interfaces, new documentation and updates to cater for any recent new releases of MS Windows.