Visualising data distributions with kernel density estimation and reduced chi-squared statistic
© 2017 China University of Geosciences (Beijing) and Peking University. The application of frequency distribution statistics to data provides objective means to assess the nature of the data distribution and viability of numerical models that are used to visualize and interpret data. Two commonly us...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/57327 |
| _version_ | 1848760053887139840 |
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| author | Spencer, Christopher Yakymchuk, C. Ghaznavi, M. |
| author_facet | Spencer, Christopher Yakymchuk, C. Ghaznavi, M. |
| author_sort | Spencer, Christopher |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2017 China University of Geosciences (Beijing) and Peking University. The application of frequency distribution statistics to data provides objective means to assess the nature of the data distribution and viability of numerical models that are used to visualize and interpret data. Two commonly used tools are the kernel density estimation and reduced chi-squared statistic used in combination with a weighted mean. Due to the wide applicability of these tools, we present a Java-based computer application called KD. X to facilitate the visualization of data and the utilization of these numerical tools. |
| first_indexed | 2025-11-14T10:09:40Z |
| format | Journal Article |
| id | curtin-20.500.11937-57327 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:09:40Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-573272017-10-30T08:35:13Z Visualising data distributions with kernel density estimation and reduced chi-squared statistic Spencer, Christopher Yakymchuk, C. Ghaznavi, M. © 2017 China University of Geosciences (Beijing) and Peking University. The application of frequency distribution statistics to data provides objective means to assess the nature of the data distribution and viability of numerical models that are used to visualize and interpret data. Two commonly used tools are the kernel density estimation and reduced chi-squared statistic used in combination with a weighted mean. Due to the wide applicability of these tools, we present a Java-based computer application called KD. X to facilitate the visualization of data and the utilization of these numerical tools. 2017 Journal Article http://hdl.handle.net/20.500.11937/57327 10.1016/j.gsf.2017.05.002 Elsevier unknown |
| spellingShingle | Spencer, Christopher Yakymchuk, C. Ghaznavi, M. Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title | Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title_full | Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title_fullStr | Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title_full_unstemmed | Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title_short | Visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| title_sort | visualising data distributions with kernel density estimation and reduced chi-squared statistic |
| url | http://hdl.handle.net/20.500.11937/57327 |