Journal of Computations & Modelling

Changepoint Detection Model based on Skew-Normal distributions for aCGH Data

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• Abstract

  In this paper we propose a changepoint detection procedure based on a skew normal distribution from the view of point of model selection. The detection procedure is constructed based on Schwarz information criterion (SIC) combined with the binary segmentation method for multiple changepoints detection purpose. Simulations are conducted to illustrate the performance of the proposed test. We apply the method to detect change points in the array Comparative Genomic Hy- bridization (aCGH) data set.