Finite-Sample Bias-Correction Factors for the Median Absolute Deviation

References

• Abu-Shawiesh, M. O.A. (2008). A simple robust control chart based on MAD. Journal of Mathematics and Statistics 4:102–107.
   Google Scholar
• Abu-Shawiesh, M.O., Al-Athari, F.M., Kittani, H.F. (2009). Confidence interval for the mean of a contaminated normal distribution. Journal of Applied Sciences 9:2835–2840.
   Google Scholar
• Adekeye, K.S., Azubuike, P.I. (2012). Derivation of the limits for control chart using the median absolute deviation for monitoring non-normal process. Journal of Mathematics and Statistics 8:37–41.
   Google Scholar
• Al-Athari, F.M. (2011). Confidence interval for locations of non-kurtosos and large kurtosis leptokurtic symmetric distributions. Journal of Applied Sciences 11:528–534.
   Google Scholar
• Birdeau, C., Gunter, B., Pikounis, B., Liaw, A. (2003). Improved statistical methods for hit selection in high-throughput screening. Journal of Biomolecular Screening 8:634–647.
   PubMed Web of Science ®Google Scholar
• Chung, N., Zhang, X.D., Kreamer, A., Locco, L., Kuan, P., Bartz, S., Linsley, P.S., Ferrer, M., Strulovici, B. (2008). Median absolute deviation to improve hit selection for genome-scale RNAi screens. Journal of Biomolecular Screening 13:149–158.
   PubMed Web of Science ®Google Scholar
• Croux, C., Rousseeuw, P.J. (1992). Time-efficient algorithms for two highly robust estimators of scale. In: Dodge, Y., Whittaker, J., eds. Computational Statistics. vol. 1. Physica-Verlag: Heidelberg, pp. 411–428.
   Google Scholar
• Hampel, F.R. (1974). The influence curve and its role in robust estimation. Journal of the American Statistical Association 69:383–393.
   Web of Science ®Google Scholar
• Iglewicz, B., Hoagline, D.C. (1993). How to Detect and Handle Outliers. The American Society for Quality Control Basic References in Quality Control: Statistical Techniques, Volume 16. Milwaukee, WI: ASQC Quality Press.
   Google Scholar
• Malinowski, E.R. (2009). Determination of rank by median absolute deviation (DRMAD): A simple method for determining the number of principal factors responsible for a data matrix. Journal of Chemometrics 23:1–6.
   Web of Science ®Google Scholar
• Malo, N., Hanley, J.A., Cerquozzi, S., Pelletier, J., Nadon, R. (2006). Statistical practice in high-throughput screening data analysis. Nature Biotechnology 24:167–175.
   PubMed Web of Science ®Google Scholar
• Matsumoto, M., Nishimura, T. (1998). Mersenne Twister: A 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Transactions on Modeling and Computer Simulation 8:3–30.
   Google Scholar
• R Development Core Team (2010). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.R-project.org/.
   Google Scholar
• Sheskin, D. (2000). Handbook of Parametric and Nonparametric Statistical Procedures. New York: Chapman & Hall.
   Google Scholar
• Smith, D.K., Radivojac, P., Obradovic, Z., Dunker, A.K., Zhu, G. (2003). Improved amino acid flexibility parameters. Protein Science 12:1060–1072.
   PubMed Web of Science ®Google Scholar
• Sprent, P., Smeeton, N.C. (2000). Applied Nonparametric Statistical Methods. New York: Chapman & Hall.
   Google Scholar
• Tukey, J.W. (1977). Exploratory Data Analysis. Reading MA: Addison-Wesley.
   Google Scholar
• Wichmann, B.A., Hill, I.D. (1982). Algorithm AS 183: An efficient and portable pseudo-random number generator. Applied Statistics 31:188–190.
   Web of Science ®Google Scholar
• Williams, D.C. (2011). Finite sample correction factors for several simple robust estimators of normal standard deviation. Journal of Statistical Computation and Simulation 81:1697–1702.
   Web of Science ®Google Scholar
• Wu, C., Zhao, Y., Wang, Z. (2002). The median absolute deviations and their applications to Shewart X control charts. Communications in Statistics—Simulation and Computation 31:425–442.
   Web of Science ®Google Scholar
• Zhang, X., Asara, J.M., Adamec, J., Ouzzani, M., Elmagarmid, A.K. (2005). Data pre-processing in liquid chromatography-mass spectrometry-based proteomics. Bioinformatics 21:4054–4059.
   PubMed Web of Science ®Google Scholar