| Автор | Lowthian, Philip J. |
| Автор | Thompson, Michael |
| Дата выпуска | 2002 |
| dc.description | Kernel density estimation is a method for producing a smooth density approximation to a dataset and avoiding some of the problems associated with histograms. If it is used with a degree of smoothing determined by a fitness for purpose criterion, it can be applied to proficiency test data in order to test for multimodality in the z-scores. The bootstrap is an essential additional technique to determine how rugged the initially estimated kernel density is: the random resampling of the data in the bootstrap simulates a complete blind repeat of the proficiency test. In addition, useful estimates of the standard error of a mode can be thus obtained. It is suggested that a mode and its standard error can be used as an assigned value and its standard uncertainty. |
| Формат | application.pdf |
| Издатель | Royal Society of Chemistry |
| Название | Bump-hunting for the proficiency tester—searching for multimodality |
| Тип | research-article |
| DOI | 10.1039/b205600n |
| Electronic ISSN | 1364-5528 |
| Print ISSN | 0003-2654 |
| Журнал | Analyst |
| Том | 127 |
| Первая страница | 1359 |
| Последняя страница | 1364 |
| Аффилиация | Lowthian Philip J.; School of Biological and Chemical Sciences, Birkbeck College (University of London) |
| Аффилиация | Thompson Michael; School of Biological and Chemical Sciences, Birkbeck College (University of London) |
| Выпуск | 10 |
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| Библиографическая ссылка | Methods Committee, Analyst, 1989, 114, 1693 |
