visualising data distributions with kernel density estimation and reduced chi-squared statistic

Visualisierung von Datenverteilungen mittels Kerndichteschätzung und reduzierter Chi-Quadrat-Statistik

Clicks: 213
ID: 129872
2017
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Abstract
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 KDX to facilitate the visualization of data and the utilization of these numerical tools.
Die Anwendung von Häufigkeitsverteilungsstatistiken auf Daten bietet ein objektives Mittel zur Beurteilung der Beschaffenheit der Datenverteilung und der Eignung numerischer Modelle, die zur Visualisierung und Interpretation von Daten eingesetzt werden. Zwei häufig verwendete Verfahren sind die Kerndichteschätzung und die reduzierte Chi-Quadrat-Statistik in Kombination mit einem gewichteten Mittelwert. Aufgrund der breiten Anwendbarkeit dieser Werkzeuge stellen wir eine Java-basierte Computeranwendung namens KDX vor, um die Visualisierung von Daten sowie die Nutzung dieser numerischen Verfahren zu erleichtern.
Reference Key
spencer2017geosciencevisualising Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;C.J. Spencer;C. Yakymchuk;M. Ghaznavi
Journal neuroscience research
Year 2017
DOI
10.1016/j.gsf.2017.05.002
URL
http://www.sciencedirect.com/science/article/pii/S1674987117300981
Keywords
data visualisation kernel density estimation

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