TY - JOUR
T1 - Estimation of Change-Point Models
AU - Bai, L.
N1 - Publisher Copyright:
© 2022, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/4
Y1 - 2022/4
N2 - We consider the testing and estimation of change-points, locations where the distribution abruptly changes, in a sequence of observations. Motivated by this problem, in this contribution we first investigate the extremes of Gaussian fields with trend, which then help us to give the asymptotic p-value approximations of the likelihood ratio statistics from change-point models.
AB - We consider the testing and estimation of change-points, locations where the distribution abruptly changes, in a sequence of observations. Motivated by this problem, in this contribution we first investigate the extremes of Gaussian fields with trend, which then help us to give the asymptotic p-value approximations of the likelihood ratio statistics from change-point models.
UR - http://www.scopus.com/inward/record.url?scp=85130740441&partnerID=8YFLogxK
U2 - 10.1007/s10958-022-05825-9
DO - 10.1007/s10958-022-05825-9
M3 - Article
AN - SCOPUS:85130740441
SN - 1072-3374
VL - 262
SP - 425
EP - 441
JO - Journal of Mathematical Sciences (United States)
JF - Journal of Mathematical Sciences (United States)
IS - 4
ER -