Change point detection by sparse parameter estimation
| Authors | |
|---|---|
| Year of publication | 2009 |
| Type | Article in Proceedings |
| Conference | Selected papers of the XIII international conference “Applied Stochastic Models and Data Analysis” (ASMDA-2009) |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.vgtu.lt/leidiniai/leidykla/ASMDA_2009/PDF/07_sec_033_Neubauer_et_al_Change.pdf |
| Field | Applied statistics, operation research |
| Keywords | change point detection; overparametrized model; sparse parameter estimation |
| Description | The contribution is focused on change point detection in one-dimensional stochastic processes by sparse parameter estimation in overparametrized models. Stochastic processes with changes in the mean are estimated by Heaviside functions. The Basis Pursuit algorithm is used to get sparse parameter estimates. The mentioned method of change point detection in stochastic processes is compared with standard methods by simulations. |
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