Abstract
A model is postulated given a short bivariate time series data with highdimensional inputs. The correlated response vectors are functions of the contemporaneous effects of the input series. The model is then estimated using a hybrid of methods embedded into the backfitting algorithm. It is noted from the simulation studies that the estimation procedure produces parameter estimates with lower relative bias and better predictive ability compared to 𝑉𝐴𝑅(1). The estimation method is also robust to misspecification errors.
Original language | English |
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Title of host publication | Proceeding of the 62nd ISI World Statistics Congress 2019 |
Subtitle of host publication | Contributed Paper Session |
Editors | Rozita Talha |
Place of Publication | Putrajaya Malaysia |
Publisher | Department of Statistics Malaysia |
Pages | 1-10 |
Number of pages | 10 |
Volume | 7 |
Publication status | Published - 2019 |
Externally published | Yes |
Event | ISI World Statistics Congress 2019 - Kuala Lumpur, Malaysia Duration: 18 Aug 2019 → 23 Aug 2019 Conference number: 62nd https://www.isi2019.org/ https://2019.isiproceedings.org/ (Proceedings) |
Conference
Conference | ISI World Statistics Congress 2019 |
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Abbreviated title | ISI 2019 |
Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 18/08/19 → 23/08/19 |
Internet address |
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