Journal of Data Science

Changepoint analysis has had a striking variety of applications, and a rich methodology has been developed. Our contribution here is a new approach that uses nonlinear regression analysis as an intermediate computational device. The tool is quite versatile, covering a number of different changepoint scenarios. It is largely free of parametric model assumptions, and has the major advantage of providing standard errors for formal statistical inference. Both abrupt and gradual changes are covered.