Statistical analysis of plant ecological and worm ethological data - Some viewpoints of explanatory variables in base models -
This thesis gives some methods for evaluating statistical data via a model selection and shows some applications of the methods. Especially, plant ecological and worm ethological data with spatial information are treated. Characteristic problems arising in each data are shown through the data analys...
| Main Authors: | , , |
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| Format: | Thesis |
| Language: | English |
| Published: |
2008
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| Subjects: | |
| Online Access: | https://ir.soken.ac.jp/?action=repository_uri&item_id=790 http://id.nii.ac.jp/1013/00000790/ |
| Summary: | This thesis gives some methods for evaluating statistical data via a model selection and shows some applications of the methods. Especially, plant ecological and worm ethological data with spatial information are treated. Characteristic problems arising in each data are shown through the data analysis of explanatory variables in base models. Firstly, the problem of selecting topographical attribute as the explanatory variable is discussed through contingency table statistics. As an example, an analysis of observed data about relative altitudes and about distribution of moss is shown. In order to consider the relationship between topography and distribution of plants, data of altitude and mosses in study plots in continental Antarctica were collected by the present author when he had a chance to visit there. The altitude data was processed as an explanatory variable of model about the existence of moss. As one of the important topographical attributes that are calculated from altitude data, the relief from standard surface was adopted. Under the assumption that the probability of moss existence is proportional to the value of residuals from standard surface, the strength of relationship between topography and moss distribution was obtained by using 2 X 2 contingency table statistics. It suggested that a simpler standard surface had a better ability, than an adjusted standard surface, of determining topographical attribute which strongly related to the moss existence. Then, the standard surface estimated by robust methods presented in this paper had a little better ability than by a prevailing least-square method. Totally, the accurate regression methods were overfitting as a method of determining the standard surface. Secondly, a modeling with spatial information is treated. The problem of selecting a model is discussed through linear models and linear mixed models. As examples, the analyses of the distribution of dwarf pine in mixed forest and of the moving track of nematode are shown. In the analysis of dwarf ... |
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