For a fuller overview of this function including a description of the CPM framework and examples of how to use the various functions, please consult the package manual "Parametric and Nonparametric Sequential Change Detection in R: The cpm Package" available from www.gordonjross.co.uk
getBatchThreshold(cpmType, alpha, n, lambda=0.3)Hawkins, D. , Zamba, K. (2005b) -- Statistical Process Control for Shifts in Mean or Variance Using a Changepoint Formulation, Technometrics, 47(2), 164-173 Hawkins, D., Qiu, P., Kang, C. (2003) -- The Changepoint Model for Statistical Process Control, Journal of Quality Technology, 35, 355-366. Ross, G. J., Tasoulis, D. K., Adams, N. M. (2011) -- A Nonparametric Change-Point Model for Streaming Data, Technometrics, 53(4) Ross, G. J., Adams, N. M. (2012) -- Two Nonparametric Control Charts for Detecting Arbitary Distribution Changes, Journal of Quality Technology, 44:102-116 Ross, G. J., Adams, N. M. (2013) -- Sequential Monitoring of a Proportion, Computational Statistics, 28(2)
Ross, G. J., (2014) -- Sequential Change Detection in the Presence of Unknown Parameters, Statistics and Computing 24:1017-1030 Ross, G. J., (2015) -- Parametric and Nonparametric Sequential Change Detection in R: The cpm Package, Journal of Statistical Software, forthcoming
detectChangePointBatch.## Returns the threshold for n=1000, alpha=0.05 and the Mann-Whitney CPM
h <- getBatchThreshold("Mann-Whitney", 0.05, 1000)Run the code above in your browser using DataLab