The robustness of the Ud-plot on assessing normality

Music City Center 

The Ad-plot developed from the cumulative average deviation function efficiently detects numerous distributional characteristics, including symmetry, skewness, and outliers analogous to sample variance plots that outperform histograms. In the meantime, the Ud-plot derived from a slight modification to the Ad-plot is outstanding in assessing normality, surpassing normal QQ-plot, normal PP-plot, and their derivations.  In this work, the robustness of the Ud-plot is explored while employing the trimmed average in the cumulative average deviation function. From the standpoint of assessing normality, the robust version is as exceptional as the Ud-plot. For actual and simulated data, the performance of the novel substitute is compared with the Ud-plot. Markedly, this version is extremely competitive in assessing normality and capturing vital distribution properties. Thus, the innovative statistical plot is a noteworthy addition to data visualization implements, delivering insightful illustrations while enhancing perception. In addition, the adplots R package will also be introduced to construct Ad-plot and Ud-plot.

Ad-plot

Ada-plot

Ud-plot

Uda-plot

Assessing Normality

Data Visualization 

Section on Statistical Graphics