Fitting multiple change-point models to data
نویسنده
چکیده
Change-point problems arise when di/erent subsequences of a data series follow di/erent statistical distributions – commonly of the same functional form but having di/erent parameters. This paper develops an exact approach for 3nding maximum likelihood estimates of the change points and within-segment parameters when the functional form is within the general exponential family. The algorithm, a dynamic program, has execution time only linear in the number of segments and quadratic in the number of potential change points. The details are worked out for the normal, gamma, Poisson and binomial distributions. c © 2001 Elsevier Science B.V. All rights reserved.
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