Toward A Common Framework for Statistical Analysis and Development
MetadataShow full item record
CitationImai, Kosuke, Gary King, and Olivia Lau. 2008. Toward A common framework for statistical analysis and development. Journal of Computational and Graphical Statistics 17(4): 892-913.
AbstractWe describe some progress toward a common framework for statistical analysis and software development built on and within the R language, including R's numerous existing packages. The framework we have developed offers a simple unified structure and syntax that can encompass a large fraction of statistical procedures already implemented in R, without requiring any changes in existing approaches. We conjecture that it can be used to encompass and present simply a vast majority of existing statistical methods, regardless of the theory of inference on which they are based, notation with which they were developed, and programming syntax with which they have been implemented. This development enabled us, and should enable others, to design statistical software with a single, simple, and unified user interface that helps overcome the conflicting notation, syntax, jargon, and statistical methods existing across the methods subfields of numerous academic disciplines. The approach also enables one to build a graphical user interface that automatically includes any method encompassed within the framework. We hope that the result of this line of research will greatly reduce the time from the creation of a new statistical innovation to its widespread use by applied researchers whether or not they use or program in R.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4215066
- FAS Scholarly Articles