Modified path algorithm of fused Lasso signal approximator for consistent recovery of change points

被引：6
|
作者：
Son, Won [1 ]
Lim, Johan [2 ]
机构：
[1] Bank Korea, 67 Sejong Daero, Seoul 04514, South Korea
[2] Seoul Natl Univ, Dept Stat, 1 Gwanak Ro, Seoul 08826, South Korea
来源：
JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2019年 / 200卷
基金：
新加坡国家研究基金会;
关键词：
Change points; Fused lasso signal approximator; Modified path algorithm; Total variation penalty;
D O I：
10.1016/j.jspi.2018.10.003
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
The path algorithm of the fused lasso signal approximator is known to fail in finding change points when monotonically increasing or decreasing blocks exist in the mean vector. In this paper, we first understand why the standard path algorithm by Hoefling (2010) fails in the primal optimization problem. We then propose a modified path algorithm for the consistent recovery of the change points and study its properties theoretically and numerically. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：223 / 238
页数：16
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