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https://doi.org/10.2498/cit.1001390

Some Analyses of Interval Data

Lynne Billard


Puni tekst: engleski pdf 840 Kb

str. 225-233

preuzimanja: 878

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Sažetak

Contemporary computers bring us very large datasets, datasets which can be too large for those same computers to analyse properly. One approach is to aggregate these data (by some suitably scientific criteria) to provide more manageably-sized datasets. These aggregated data will perforce be symbolic data consisting of lists, intervals, histograms, etc. Now an observation is a p-dimensional hypercube or Cartesian product of p distributions in Rp, instead of the p-dimensional point in Rp of classical data. Other data can be naturally symbolic. We give a brief overview of interval-valued data and show briefly that it is important to use symbolic analysis methodology since, e.g., analyses based on classical surrogates ignore some of the information in the dataset.

Ključne riječi

Hrčak ID:

44574

URI

https://hrcak.srce.hr/44574

Datum izdavanja:

30.12.2008.

Posjeta: 1.328 *