Sööt
Biographic Data
| ID | 3719633 |
|---|---|
| NAME | Sööt |
| FAMILY NAME | Sööt |
| SIGNATURE | SÖÖT |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1977 |
| LATEST PUBLICATION YEAR | 1977 |
| H-INDEX | 1 |
Rank Tests for Spatial Correlation
If spatial data do not have an underlying normal distribution, the traditional tests for spatial correlation may lead to erroneous conclusions. This is illustrated by means of an example. A class of tests based on the ranks of the observations is proposed and the large sample normality of each test is established. A theorem providing the basis for locally most powerful tests is also presented
Rank Tests for Spatial Correlation
If spatial data do not have an underlying normal distribution, the traditional tests for spatial correlation may lead to erroneous conclusions. This is illustrated by means of an example. A class of tests based on the ranks of the observations is proposed and the large sample normality of each test is established. A theorem providing the basis for locally most powerful tests is also presented
Rank Tests for Spatial Correlation
If spatial data do not have an underlying normal distribution, the traditional tests for spatial correlation may lead to erroneous conclusions. This is illustrated by means of an example. A class of tests based on the ranks of the observations is proposed and the large sample normality of each test is established. A theorem providing the basis for locally most powerful tests is also presented
Bayesian Methods and Mixture Models (1 work) · Combinatorics (1 work) · Correlation (1 work) · Geometry (1 work) · Mathematics (1 work) · Normality (1 work) · Normality test (1 work) · Physics (1 work) · Rank correlation (1 work) · Spatial analysis (1 work)