A Unified Bootstrap Test for Local Patterns of Spatiotemporal Association
Bibliographic Data
| ID | 4139580 |
|---|---|
| Authors | N A Yan (Xi'an Jiaotong University), Na Yan (0000-0003-2160-5028, Xi'an Jiaotong University, corresponding author), Chang-Lin Mei (Xi'an Jiaotong University), Changlin Mei (0000-0002-4663-7993, Xi'an Jiaotong University, corresponding author), Ning Wang (0009-0007-8931-918X, Xi'an Jiaotong University, corresponding author) |
| Year | 2015 |
| Volume | 47 |
| Issue | 1 |
| Pages | 227-242 |
| Publication date | 2015-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning A Economy and Space (JOURNAL) |
| Journal identifiers | ISSN: 0308-518X • E-ISSN: 1472-3409 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1068/a130063p |
| OpenAlex | W2057799540 |
| Language | EN |
| Citations received | 1 |
| References cited | 19 |
There has been a growing interest in using local statistics to identify spatial or spatiotemporal association patterns among georeferenced data, in which the null distributions of the statistics play a key role for the confirmatory inferences. In this study we focus on a generic form of local spatiotemporal statistics and propose a unified bootstrap approach to derive the null distribution of the statistic. In particular, the spatiotemporal variants of the commonly used local spatial statistics Moran's Ii, Geary's ci, and Getis and Ord's Gi are studied in detail. Some simulations are conducted to evaluate the validity of the bootstrap method in approximating the null distributions of the three spatiotemporal statistics. Meanwhile, the bootstrap method is compared with the permutation approach in terms of approximation accuracy and computation efficiency. The results show that both the bootstrap and the permutation methods can accurately approximate the null distributions of the statistics for various spatiotemporal topological relationships while the bootstrap method seems to be more efficient than the permutation approach. Additionally, the power of the spatiotemporal version of Moran's Ii in detecting spatiotemporal autocorrelation is empirically assessed and a real-world example is given to demonstrate the application of the bootstrap inference method
Autocorrelation · Combinatorics · Data mining · Inference · Null distribution · Null hypothesis · Null model · Resampling · Spatial analysis · Statistic · Statistical hypothesis testing · Statistics · Test statistic · Computer Science · Data-Driven Disease Surveillance · Land Use and Ecosystem Services · Mathematics · Spatial and Panel Data Analysis · Artificial Intelligence
Local Spatial Autocorrelation Statistics
Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices
Bootstrap Methods
Controlling the False Discovery Rate
Controlling the False Discovery Rate
The Analysis of Spatial Association by Use of Distance Statistics
Effects of randomization methods on statistical inference in disease cluster detection
Some Practical Applications of Moran's I's Exact Conditional Distribution
Local Indicators of Spatial Association—Lisa
Spatial Interaction and Spatial Autocorrelation
Statistical Test for Local Patterns of Spatial Association
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |