A Modified Spatiotemporal Mixed-Effects Model for Interpolating Missing Values in Spatiotemporal Observation Data Series
Joint Authors
Dai, Wujiao
Shi, Qiang
Santerre, Rock
Liu, Ning
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-10
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Missing values in data series is a common problem in many research and applications.
Most of existing interpolation methods are based on spatial or temporal interpolation, without considering the spatiotemporal correlation of observation data, resulting in poor interpolation effect.
In this paper, a Modified Spatiotemporal Mixed-Effects (MSTME) model for interpolation of spatiotemporal data series is proposed.
Experiments with simulated data and real SCIGN data are performed to assess the validity of the proposed model in comparison with Kriged Kalman Filter (KKF) model and Spatiotemporal Mixed-Effects (STME) model.
The average improvements of simulated data and SCIGN data for observed stations are around 46% and 19% over the KKF model and 62% and 21% over the STME model, and those for unobserved stations are around 23% and 34% over the KKF model and 41% and 16% over the STME model, respectively, indicating that the proposed MSTME model can achieve better accuracy for interpolating missing values.
American Psychological Association (APA)
Shi, Qiang& Dai, Wujiao& Santerre, Rock& Liu, Ning. 2020. A Modified Spatiotemporal Mixed-Effects Model for Interpolating Missing Values in Spatiotemporal Observation Data Series. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1193034
Modern Language Association (MLA)
Shi, Qiang…[et al.]. A Modified Spatiotemporal Mixed-Effects Model for Interpolating Missing Values in Spatiotemporal Observation Data Series. Mathematical Problems in Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1193034
American Medical Association (AMA)
Shi, Qiang& Dai, Wujiao& Santerre, Rock& Liu, Ning. A Modified Spatiotemporal Mixed-Effects Model for Interpolating Missing Values in Spatiotemporal Observation Data Series. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1193034
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193034