@article{MAKHILLRJAS20161199859,
    title = {Robust Estimation of Circular Parameters},
    journal = {Research Journal of Applied Sciences},
    volume = {11},
    number = {9},
    pages = {870-873},
    year = {2016},
    issn = {1815-932x},
    doi = {rjasci.2016.870.873},
    url = {https://makhillpublications.co/view-article.php?issn=1815-932x&doi=rjasci.2016.870.873},
    author = {Ehab A.,Habshah and},
    keywords = {Outliers,robust statistics,circular variance,mean resultant length,resultant,length},
    abstract = {Researchers interest to develop methods of robust estimation. These methods can be used when the data have outliers or not satisfy the condition of classical methods. However, few researchers suggest robust estimation of circular data. In this study, we propose robust estimation of circular variance and mean resultant length. The proposed robust estimation depends on extending trimmed procedure by find robust formula for trimming. Simulation results and practical example show that the proposed procedure for the circular variance and mean resultant length are better than classical methods for different ratios of outliers.}
    }