000			01484nam a22002057a 4500
003			CHED
005			20240425163253.0
008			240123b |||||||| |||| 00| 0 eng d
040			_cCommission on Higher Education
050			_aLG 995 2018 C6 A73
100			_aAracid, Sarah Bernadette M.
245			_aUnit root test in a semiparametric model _cSarah Bernadette M. Aracid
260			_aDiliman, Quezon City _b : University of the Philippines _c,2018.
300			_aii, 55 pages _c ; 29 cm. _ewith CD.
500			_aThesis (Master of Science major in Statistics) -- University of the Philippines Diliman, June 2018.
520			_aPresence 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.
650			_aEmpirical distribution.
650			_aNonparametric test.
942			_2lcc _cTD _n0
999			_c7262 _d7262