LASSO estimation for spherical autoregressive processes

被引：5
|
作者：
Caponera, Alessia [1 ,2 ]
Durastanti, Claudio [3 ]
Vidotto, Anna [2 ,4 ]
机构：
[1] Sapienza Univ Roma, Dipartimento Sci Stat, Rome, Italy
[2] Univ Roma Tor Vergata, Dipartimento Matemat, Rome, Italy
[3] Sapienza Univ Roma, Dipartimento SBAI, Rome, Italy
[4] Univ G DAnnunzio, Dipartimento Econ, Chieti, Italy
来源：
STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2021年 / 137卷 / 137期
关键词：
Spherical functional autoregressions; LASSO method; Kernel estimation; Stability; Consistency; Oracle inequalities; GAUSSIAN RANDOM-FIELDS; COVARIANCE FUNCTIONS; REGRESSION; REGULARITY;
D O I：
10.1016/j.spa.2021.03.009
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 purpose of the present paper is to investigate a class of spherical functional autoregressive processes in order to introduce and study LASSO (Least Absolute Shrinkage and Selection Operator) type estimators for the corresponding autoregressive kernels, defined in the harmonic domain by means of their spectral decompositions. Some crucial properties for these estimators are proved, in particular, consistency and oracle inequalities. (C) 2021 Elsevier B.V. All rights reserved.
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页码：167 / 199
页数：33
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