Structure learning: some testing problems
The work is based on data about the prevalence of congenital anomalies among newborns in Lithuania. The log-linear model is used to assess dependence structure of a subset of categorical variables. It is shown that fitting the log-linear model with just three categorical variables can be a rather c...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Vilnius University Press
2005-12-01
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| Series: | Lietuvos Matematikos Rinkinys |
| Subjects: | |
| Online Access: | https://www.journals.vu.lt/LMR/article/view/27388 |
| Summary: | The work is based on data about the prevalence of congenital anomalies among newborns in Lithuania. The log-linear model is used to assess dependence structure of a subset of categorical variables. It is shown that fitting the log-linear model with just three categorical variables can be a rather complicated task due to large number of unknown parameters and cells in the contingency table. The classical chi-squre test and the bootstrap technique are compared for testing goodness-of-fit. The results demonstrate that the number of cells of even nonsparse contingency tables has significant impact on the tail distribution of the likelihood ratio statistics.
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| ISSN: | 0132-2818 2335-898X |