Validation of causal inference data using DirectLiNGAM in an environmental small-scale model and calculation settings.

ABSTRACT: The development of data science has been needed in environmental fields such as marine, weather, and soil data. In general, the datasets are large in some cases, but they are often small because they contain observation data that the analyses themselves are limited. In such a case, the data are statistically evaluated by increasing or decreasing the levels of factors using differential analysis, resulting in the essential factors are estimated. However, there is no consistent approach to the means of assessing strong associations as a group between factors. Causal inference method has the possibility to output effective results for small data, and the results are expected to provide important information for understanding the potential highly association between factors, not necessarily th

SUBMITTER: Kurotani A 

PROVIDER: S-EPMC10809110 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature