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- Title
Nonparametric prediction for univariate spatial data: Methods and applications.
- Authors
Arancibia, Rodrigo García; Llop, Pamela; Lovatto, Mariel
- Abstract
We introduce five nonparametric kriging‐type predictors for spatial data where only the variable of interest, without covariates, is recorded. The proposed methods seek to fully exploit the information contained in the spatial closeness and also in the similarity between neighbourhoods of the variable of interest. This is managed using different combinations of kernels (one or two kernels), and different combinations of distances (multiplicative and additive). The good performance of the proposed methods is shown via simulation studies and housing price prediction applications.
- Subjects
HOME prices; FORECASTING; NEIGHBORHOODS
- Publication
Papers in Regional Science, 2023, Vol 102, Issue 3, p635
- ISSN
1056-8190
- Publication type
Article
- DOI
10.1111/pirs.12735