Unit root test in a semiparametric model Sarah Bernadette M. Aracid
Material type:
- LG 995 2018 C6 A73
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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Commission on Higher Education Thesis | Thesis and Dissertation | LG 995 2018 C6 A73 (Browse shelf(Opens below)) | 1 | Available (Room Use Only) | CHEDTD-000083 | ||
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Commission on Higher Education Digital Thesis and Dissertation | Digital Thesis and Dissertation | LG 995 2018 C6 A73 (Browse shelf(Opens below)) | 1 | Storage Area (Restricted Access) | DCHEDTD-000024 |
Thesis (Master of Science major in Statistics) -- University of the Philippines Diliman, June 2018.
Presence of unit root in time series data is implicated in the persistent effect of random shocks in the behavior of a model, leading most unit root tests to be incorrectly-sized or have low power or both. A nonparametric test for the presence of unit root is proposed. To mitigate the possible problem of present unit root tests, it is assumed that another time series (x,t) possibly affect the target time series (y,t) in addition to the autocorrelation dynamics. A nonparametric effect of (x,t) can spare the autocorrelation structure from further contaminations, hence, the test can characterize presence of unit roots in yt easily. Simulation study showed that the proposed test yields better size and power compared to some tests for unit root.
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