Model-building with interpolated temporal data

doi:10.1016/j.ecoinf.2006.02.005

Model-building with interpolated temporal data

2006-11-01

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DOI：10.1016/j.ecoinf.2006.02.005

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Ecological data can be difficult to collect, and as a result, some important temporal ecological datasets contain irregularly sampled data. Since many temporal modelling techniques require regularly spaced data, one common approach is to linearly interpolate the data, and build a model from the interpolated data. However, this process introduces an unquantified risk that the data is over-fitted to the interpolated (and hence more typical) instances. Using one such irregularly-sampled dataset, the Lake Kasumigaura algal dataset, we compare models built on the original sample data, and on the interpolated data, to evaluate the risk of mis-fitting based on the interpolated data. (c) 2006 Elsevier B.V. All rights reserved.

Keyword:

linear interpolation

modelling

genetic programming

Model-building with interpolated temporal data

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