TY - JOUR
T1 - Local asymptotic normality for regression models with long-memory disturbance
AU - Hallin, Marc
AU - Taniguchi, Masanobu
AU - Serroukh, Abdeslam
AU - Choy, Kokyo
PY - 1999/12
Y1 - 1999/12
N2 - The local asymptotic normality property is established for a regression model with fractional ARIMA(p, d, q) errors. This result allows for solving, in an asymptotically optimal way, a variety of inference problems in the long-memory context: hypothesis testing, discriminant analysis, rankbased testing, locally asymptotically minimax and adaptive estimation, etc. The problem of testing linear constraints on the parameters, the discriminant analysis problem, and the construction of locally asymptotically minimax adaptive estimators are treated in some detail.
AB - The local asymptotic normality property is established for a regression model with fractional ARIMA(p, d, q) errors. This result allows for solving, in an asymptotically optimal way, a variety of inference problems in the long-memory context: hypothesis testing, discriminant analysis, rankbased testing, locally asymptotically minimax and adaptive estimation, etc. The problem of testing linear constraints on the parameters, the discriminant analysis problem, and the construction of locally asymptotically minimax adaptive estimators are treated in some detail.
KW - Adaptive estimation
KW - Discriminant analysis
KW - FARIMA model
KW - Local asymptotic normality
KW - Locally asymptotically optimal test
KW - Long-memory process
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M3 - Article
AN - SCOPUS:0033234638
VL - 27
SP - 2054
EP - 2080
JO - Annals of Statistics
JF - Annals of Statistics
SN - 0090-5364
IS - 6
ER -