Linear Trend Filtering via Adaptive LASSO

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10384379" target="_blank" >RIV/00216208:11320/18:10384379 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-96944-2" target="_blank" >http://dx.doi.org/10.1007/978-3-319-96944-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-96944-2" target="_blank" >10.1007/978-3-319-96944-2</a>

Result language
angličtina
Original language name
Linear Trend Filtering via Adaptive LASSO
Original language description
Linear trend filtering methods are popular due to their over- all simplicity - the model is linear in each segment and there are typi- cally only few segments considered. These segments are defined by unique points where the trend changes its direction - so called changepoints. In this paper we consider an innovative estimation approach for such mod- els. Our proposal is based on recent developments in the atomic pursuit techniques: we present an estimation algorithm based on the adaptive LASSO penalty and we introduce a fully data-driven method which can be effectively used to fit the continuous linear trend models. Some statis- tical properties are discussed and the empirical performance is compared with respect to other competitive LASSO based techniques.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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