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NEWS

• The associated paper is now accepted for publication in Biometrika: see doi:10.1093/biomet/asaf024 for full details.
• Updated multiscale.np.mojo() function so that returned cpts are given in time order.
• The p-values returned by np.mojo(), np.mojo.multilag(), and mulsticale.np.mojo() have been replaced by importance scores: when the bootstrap is used, these are essentially one minus the p-value. Larger scores give more evidence of a change point.
• Fixed error that occurs when using the manual threshold and the np.mojo.multilag() function, thanks to Chuanyang Zhang for spotting this.
• You can now use different manual thresholds for different lags: for use in np.mojo.multilag(), you can supply a vector, whilst for mulsticale.np.mojo(), you can supply a list of vectors.
• Added package level documentation: see ?CptNonPar.

• Updated link to the paper in description to comply with CRAN check.

• Added a new function multiscale.np.mojo(), this function performs multiscale, multi-lag nonparametric change point detection using a set of bandwidths (as opposed to a single bandwidth as in np.mojo.mulilag()).
• Updated parallelisation code in np.mojo() to avoid unnecessary call to closeAllConnections(), thanks to Henrik Bengtsson for highlighting this.
• Changed uses of itemize in .Rd files to comply with CRAN check.

• Updated description field in Description file.
• Updated examples in np.mojo, np.mojo.multilag, and multilag.cpts.merge.

• Added a NEWS.md file to track changes to the package.

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