Change Point Detection by Sparse Parameter Estimation
| Authors | |
|---|---|
| Year of publication | 2011 |
| Type | Article in Periodical |
| Magazine / Source | Informatica |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.mii.lt/informatica/pdf/INFO812.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 a one-dimensional stochastic process by sparse parameter estimation from an overparametrized model. A stochastic process with change in the mean is estimated using dictionary consisting of Heaviside functions. The basis pursuit algorithm is used to get sparse parameter estimates. The mentioned method of change point detection in a stochastic process is compared with several standard statistical methods by simulations. |
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