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• W3048113364 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." @default.
• W3048113364 created "2020-08-13" @default.
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• W3048113364 date "2022-05-23" @default.
• W3048113364 modified "2023-09-30" @default.
• W3048113364 title "NONPARAMETRIC PREDICTION WITH SPATIAL DATA" @default.
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• W3048113364 doi "https://doi.org/10.1017/s0266466622000226" @default.
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