Testing a large number of multinomial two-sample problems with application in digital elevation models

M. V. Alba Fernández, M. D. Jiménez Gamero

A Digital Elevation Model (DEM) is a bare earth elevation model representing the surface of the Earth. To compare two DEMs, a multivariate and spatialized perspective is proposed. This way, to determine whether two DEMs can be considered as similar: (i) a spatialization (natural or artificial) of the study area is needed, (ii) from each spatial unit, the same categorized variable is derived from each DEM for further comparison, and (iii) the similarity between two DEMs will be equivalent to test a large number of the equalities of categorized variables. A test statistic based on the Euclidean distance between the estimated proportions in each pair of populations is designed. The null distribution of the test statistic is unknown and its asymptotic null distribution is derived. A simulation study is carried out to evaluate the behaviour of the proposal in a wide range of scenarios. Finally, an application to two DEM datasets from the same zone (Allo, Navarra, Spain) is detailed.

Keywords: Euclidean distance, two-sample, multinomial

Scheduled

Invited Session Recent advances in goodness-of-fit and k-sample tests
June 10, 2022  10:10 AM
A13

Other papers in the same session

On automatic kernel density estimate-based tests for goodness-of-fit

C. Tenreiro

Testing for order among K binomial populations

A. M. Franco Pereira, M. C. Pardo Llorente, C. T. Nakas

Goodness-of-fit testing with doubly truncated data: some recent developments

J. de Uña Álvarez

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