Model Search in Contingency Tables by CoCo
J.H. Badsberg · Computational Statistics · 1992
CoCo 1 , a highly advanced program for analysis of complete and incomplete contingency tables, is presented. In the paper a short presentation of CoCo is given. Incremental search by backward elimination and forward selection and the global search procedure from Edwards & Havránek (1985) is considered. By incremental search a single minimal acceptable model is identified. By the principles of weakly accepted and weakly rejected the class of minimal acceptable models are found in the global search procedure. In CoCo each of the model searches can be done by a single command, or CoCo can be guided through the search in a highly user controlled model selection. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.