Group lassoing change-points in piecewise-constant AR processes

Group lassoing change-points in piecewise-constant AR processes

Regularizing the least-squares criterion with the total number of coefficient changes, it is possible to estimate timevarying (TV) autoregressive (AR) models with piecewise-constant coefficients. Such models emerge in various applications including speech segmentation, biomedical signal processing, and geophysics. To cope with the inherent lack of continuity and the high computational burden wh...

Group lassoing change-points in piecewise-constant AR

Regularizing the least-squares criterion with the total number of coefficient changes, it is possible to estimate timevarying (TV) autoregressive (AR) models with piecewise-constant coefficients. Such models emerge in various applications including speech segmentation, biomedical signal processing, and geophysics. To cope with the inherent lack of continuity and the high computational burden wh...

Detecting multiple change points in piecewise constant hazard functions.

The National Cancer Institute (NCI) suggests a sudden reduction in prostate cancer mortality rates, likely due to highly successful treatments and screening methods for early diagnosis. We are interested in understanding the impact of medical breakthroughs, treatments, or interventions, on the survival experience for a population. For this purpose, estimating the underlying hazard function, wit...

Piecewise Constant Controlled Linear Fuzzy Systems

Detecting change-points in multidimensional stochastic processes

Ageneral test statistic for detecting change-points inmultidimensional stochastic processes with unknown parameters is proposed. The test statistic is specialized to the case of detecting changes in sequences of covariance matrices. Large-sample distributional results are presented for the test statistic under the null hypothesis of no-change. The finite-sample properties of the test statistic ...