Page 152 - Contributed Paper Session (CPS) - Volume 3
P. 152
CPS1973 Matúš M. et al.
7. Harchaoui, Z. and L´evy-Leduc, C. (2010), “Multiple Change-Point
Estimation With a Total Variation Penalty.” Journal of the American
Statistical Association, 105, No.492, 1480 – 1493.
8. Hotv´ath, L. and Kokoszka, P. (2002), “Change-Point Detection With Non-
Parametric Regression.” Statistics 36, No.1, 9-31(23).
9. Huˇskov´a, M. and Maciak, M. (2017), “Discontinuities in Robust
Nonparametric Regression with A-mixing Dependence.” Journal of
Nonparametric Statistics 29, No.2, 447-475.
10. Jacob, L., Obozinski, G. and Vert, J.P. (2009), “Group Lasso with Overlap
and Graph Lasso.” Proceedings of he 26th International Conference on
Machine Learning (ICML 26), Montreal, Canada.
11. Loader, C. (1996), “Change Point Estimation Using Nonparametric
Regression.” Annals of Statistics 24, 1667– 1678.
12. Maciak, M. and Mizera, I. (2016), “Regularization Techniques in Joinpoint
Regression.” Statistical Papers, 1-17.
13. Maciak, M. and Mizera, I. (2019), “Splines with Changepoints: Additive
Models for Functional Data.” (to be submitted).
14. M¨uller, H. (1992), “Change Points in Nonparametric Regression
Analysis.” Annals of Statistics 20, 737 – 715.
15. Qiu, P. and Yandell, B. (1998), “A Local Polynomial Jump Detection
Algorithm in Nonparametric Regression.” Technometrics 40, 141 – 152.
16. Sadhanala, V. and Tibshirani, R. (2018), “Additive Models with Trend
Filtering.” arXiv:1702.05037, 1–63.
17. Tibshirani, R. (2014), “Adaptive Piece-wise Polynomial Estimation via
Trend Filtering.” The Annals of Statistics, 42(1), 285–323.
141 | I S I W S C 2 0 1 9