Gupta, Abhimanyu and Hidalgo, Javier (2022) 'Nonparametric prediction with spatial data.' Econometric Theory. pp. 1-39. ISSN 0266-4666
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Official URL: https://doi.org/10.1017/S0266466622000226
Abstract
We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorization of the spectral density function. We provide theoretical results showing that the predictor has desirable asymptotic properties. Finite sample performance is assessed in a Monte Carlo study that also compares our algorithm to a rival nonparametric method based on the infinite AR representation of the dynamics of the data. Finally, we apply our methodology to predict house prices in Los Angeles.
Item Type: | Article |
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Uncontrolled Keywords: | Lattice data; unilateral models; canonical factorization; spectral density; nonparametric prediction |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Economics, Department of |
SWORD Depositor: | Elements |
Depositing User: | Elements |
Date Deposited: | 25 Mar 2022 10:52 |
Last Modified: | 22 Jun 2022 12:58 |
URI: | http://repository.essex.ac.uk/id/eprint/32564 |
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