Visualization of Skewed Data: A Tool in R

• RAYDONAL OSPINA ^[1] ; ANTONIO MARCOS LARANGEIRAS ^[2] ; ALEJANDRO C. FRERY ^[2]
  1. [1] Universidade Federal de Pernambuco

     Universidade Federal de Pernambuco

     Brasil

     
  2. [2] Universidade Federal de Alagoas

     Universidade Federal de Alagoas

     Brasil

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 37, Nº. 2, 2014, págs. 399-417
• Idioma: inglés
• DOI: 10.15446/rce.v37n2spe.47945
• Títulos paralelos:
  • Visualización de datos sesgados: una herramienta en R
• Enlaces
  • Texto completo
• Resumen
  • español

    Despu\es de discutir las principales características del histograma y de un número de variables en el boxplot, se presento una herramienta de visualisación específicamente diseñada para el tratamiento de datos. La idea es usar varios tipos de boxplots (el clásico, el cual es adaptado para la consideración de sesgo de los datos, el boxplot trasladado, y el gráfico de cajas de percentiles), el gráfico violin, y el histograma con un estimador no paramétrico de la densidad. Los gráficos son presentados de forma que faciliten la extracción de información adicional. Se muestra como una buena cantidad de información que puede ser extraída a través de ejemplos de imágenes de radar de apertura sintética. Se presenta su implementacón en R basada en funciones actualmente disponibles.

  • English

    After discussing the main characteristics of the histogram and of a number of variations in the boxplot, this work presents a visualization tool specifically tailored to deal with skewed data. The idea is to use various types of boxplots (the classical one, which is tuned for skewness of the data, the shifting boxplot, and the box-percentile plot), the violin plot, and the histogram with a nonparametric estimate of the density overlay. The plots are presented in such a way that they facilitate the extraction of additional information from each one. We show that a good deal of information can be extracted from the inspection of the output using example data from synthetic aperture radar images. We provide an implementation in R based on functions already available.

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