A Robust Skewed Boxplot for Detecting Outliers in Rainfall Observations in Real-Time Flood Forecasting
The standard boxplot is one of the most popular nonparametric tools for detecting outliers in univariate datasets. For Gaussian or symmetric distributions, the chance of data occurring outside of the standard boxplot fence is only 0.7%. However, for skewed data, such as telemetric rain observations...
Saved in:
Main Authors: | Chao Zhao, Jinyan Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2019-01-01
|
Series: | Advances in Meteorology |
Online Access: | http://dx.doi.org/10.1155/2019/1795673 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Uncertainty of Flood Forecasting Based on Radar Rainfall Data Assimilation
by: Xinchi Chen, et al.
Published: (2016-01-01) -
Outlier Detection Method of Dam Monitoring Data Based on Robust Estimation and Variable Separation
by: LIANG Huibin, et al.
Published: (2024-01-01) -
Study on the Method of Real Time Flood Forecasting Correction for Fengshuba Reservoir
by: 宋星原, et al.
Published: (2000-01-01) -
Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases
by: Xin Liu, et al.
Published: (2018-01-01) -
Fast Ways to Detect Outliers
by: Emad Obaid Merza, et al.
Published: (2021-03-01)