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Change-Point Monitoring in Linear Models
Oleh:
Aue, Alexander
;
Horvath, Lajos
;
Huskova, Marie
;
Kokoszka, Piotr
Jenis:
Article from Journal - ilmiah internasional
Dalam koleksi:
The Econometrics Journal vol. 9 no. 3 (2006)
,
page 373-403.
Topik:
LINEAR
;
heteroskedastic errors
;
linear model
;
prediction errors
;
on - line change - point detection
;
residuals
Fulltext:
373.pdf
(369.31KB)
Ketersediaan
Perpustakaan Pusat (Semanggi)
Nomor Panggil:
EE39.2
Non-tandon:
1 (dapat dipinjam: 0)
Tandon:
tidak ada
Lihat Detail Induk
Isi artikel
We consider a linear regression model with errors modelled by martingale difference sequences, which include heteroskedastic augmented GARCH processes. We develop asymptotic theory for two monitoring schemes aimed at detecting a change in the regression parameters. The first method is based on the CUSUM of the residuals and was studied earlier in the context of independent identically distributed errors. The second method is new and is based on the squares of prediction errors. Both methods use a training sample of size m. We show that, as m ? 8 , both methods have correct asymptotic size and detect a change with probability approaching unity. The methods are illustrated and compared in a small simulation study.
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