Statistical methods for analyzing economic data need to be timely, accurate and easy to compute. To accomplish this parametric models are often assumed, but they are at best approximate, and often lack a good fit in the tails of the distribution where much of the interesting data is concentrated. Therefore nonparametric methods have been extensively examined as alternatives to the constrictive assumptions of parametric models. This paper examines the use of Sequential Normal Scores (SNS) for detecting outliers (out-of-control values), and how they can be integrated within CUSUMs and Exponentially Weighted Moving Average (EWMA) schemes.
Conover, W., Tercero-Gomez, V. G., & Cordero-Franco, A. E. (2018). A Look at Sequential Normal Scores and How They Apply to Financial Data Analysis. Journal of Applied Mathematics and Physics, 40. https://doi.org/10.4236/jamp.2018.64069