Permutation Methods: A Distance Function Approach
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2001
|
| Series: | Springer Series in Statistics
|
| Subjects: | |
| Online Access: | Volltext |
| Item Description: | The introduction of permutation tests by R. A. Fisher relaxed the paramet ric structure requirement of a test statistic. For example, the structure of the test statistic is no longer required if the assumption of normality is removed. The between-object distance function of classical test statis tics based on the assumption of normality is squared Euclidean distance. Because squared Euclidean distance is not a metric (i. e. , the triangle in equality is not satisfied), it is not at all surprising that classical tests are severely affected by an extreme measurement of a single object. A major purpose of this book is to take advantage of the relaxation of the struc ture of a statistic allowed by permutation tests. While a variety of distance functions are valid for permutation tests, a natural choice possessing many desirable properties is ordinary (i. e. , non-squared) Euclidean distance. Sim ulation studies show that permutation tests based on ordinary Euclidean distance are exceedingly robust in detecting location shifts of heavy-tailed distributions. These tests depend on a metric distance function and are reasonably powerful for a broad spectrum of univariate and multivariate distributions. Least sum of absolute deviations (LAD) regression linked with a per mutation test based on ordinary Euclidean distance yields a linear model analysis which controls for type I error |
| Physical Description: | 1 Online-Ressource (XV, 353 p) |
| ISBN: | 9781475734492 9781475734515 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/978-1-4757-3449-2 |
Staff View
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| indexdate | 2024-07-10T01:21:09Z |
| institution | BVB |
| isbn | 9781475734492 9781475734515 |
| issn | 0172-7397 |
| language | English |
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| spelling | Mielke, Paul W. Verfasser aut Permutation Methods A Distance Function Approach by Paul W. Mielke, Kenneth J. Berry New York, NY Springer New York 2001 1 Online-Ressource (XV, 353 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 The introduction of permutation tests by R. A. Fisher relaxed the paramet ric structure requirement of a test statistic. For example, the structure of the test statistic is no longer required if the assumption of normality is removed. The between-object distance function of classical test statis tics based on the assumption of normality is squared Euclidean distance. Because squared Euclidean distance is not a metric (i. e. , the triangle in equality is not satisfied), it is not at all surprising that classical tests are severely affected by an extreme measurement of a single object. A major purpose of this book is to take advantage of the relaxation of the struc ture of a statistic allowed by permutation tests. While a variety of distance functions are valid for permutation tests, a natural choice possessing many desirable properties is ordinary (i. e. , non-squared) Euclidean distance. Sim ulation studies show that permutation tests based on ordinary Euclidean distance are exceedingly robust in detecting location shifts of heavy-tailed distributions. These tests depend on a metric distance function and are reasonably powerful for a broad spectrum of univariate and multivariate distributions. Least sum of absolute deviations (LAD) regression linked with a per mutation test based on ordinary Euclidean distance yields a linear model analysis which controls for type I error Statistics Mathematical statistics Statistical Theory and Methods Statistik Resampling (DE-588)4288033-6 gnd rswk-swf Randomisierter Test (DE-588)4294178-7 gnd rswk-swf Resampling (DE-588)4288033-6 s 1\p DE-604 Randomisierter Test (DE-588)4294178-7 s 2\p DE-604 Berry, Kenneth J. Sonstige oth https://doi.org/10.1007/978-1-4757-3449-2 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Mielke, Paul W. Permutation Methods A Distance Function Approach Statistics Mathematical statistics Statistical Theory and Methods Statistik Resampling (DE-588)4288033-6 gnd Randomisierter Test (DE-588)4294178-7 gnd |
| subject_GND | (DE-588)4288033-6 (DE-588)4294178-7 |
| title | Permutation Methods A Distance Function Approach |
| title_auth | Permutation Methods A Distance Function Approach |
| title_exact_search | Permutation Methods A Distance Function Approach |
| title_full | Permutation Methods A Distance Function Approach by Paul W. Mielke, Kenneth J. Berry |
| title_fullStr | Permutation Methods A Distance Function Approach by Paul W. Mielke, Kenneth J. Berry |
| title_full_unstemmed | Permutation Methods A Distance Function Approach by Paul W. Mielke, Kenneth J. Berry |
| title_short | Permutation Methods |
| title_sort | permutation methods a distance function approach |
| title_sub | A Distance Function Approach |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistik Resampling (DE-588)4288033-6 gnd Randomisierter Test (DE-588)4294178-7 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistik Resampling Randomisierter Test |
| url | https://doi.org/10.1007/978-1-4757-3449-2 |
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