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SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS
SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS
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SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS
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SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS
SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS
Journal Article

SPATIAL-TEMPORAL MODEL WITH HETEROGENEOUS RANDOM EFFECTS

2023
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Overview
In this paper, we propose a novel spatial-temporal model with individual random effects characterized by a location-scale structure, which allows us to flexibly capture the pure influence of space-specific factors in a quantile regression framework. A hybrid two-stage estimation procedure is introduced for this model. The first stage proposes a Gaussian quasi-maximum likelihood estimator for the spatial-temporal effects, and the second constructs a weighted conditional quantile estimator, which we use to study the conditional quantiles of the random effects related to space-specific attributes. We verify the validity of the two-stage hybrid estimation, and establish the asymptotic properties of our estimators. The results of our simulation study indicate that the proposed estimation procedure performs well in different scenarios with finite-samples. Lastly, we apply the proposed method to data from a real case study on the air quality of China.
Publisher
Institute of Statistical Science, Academia Sinica

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