Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat
In order to test whether or not the intervention effect, δ which occurs between the pre-time series and the post-time series in an intervention time series model is different from zero, under appropriate assumptions. the t- statistics test suggested by Glass, Wilson, and Gottman (2) may be used. In...
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Universiti Teknologi MARA, Pahang
1988
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| _version_ | 1833073216303661056 |
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| author | Mamat, Illias |
| author_facet | Mamat, Illias |
| author_sort | Mamat, Illias |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In order to test whether or not the intervention effect, δ which occurs between the pre-time series and the post-time series in an intervention time series model is different from zero, under appropriate assumptions. the t- statistics test suggested by Glass, Wilson, and Gottman (2) may be used. In this study. the first order autoregressive ARIMA (1,0,0,L,δ) intervention model. which contains the same pre- and post- intervention first-order autoregressive parameter Ø, is chosen in order to study the validity of the t-statistics. The variable Z will represent the series measured across n equally spaced units of time. This series is labelled as Z1,Z2-····,Zn. We shall assume the intervention effect occurs between times n1 and n1 + 1. where n1 < n. and where L is the level of the pre- intervention time series Z1,Z2 , Zn1' and (L+δ) is the level of post-intervention time series Znl+1, ,Zn. Zinkgraft and Wilson [5] simulated the performance of this t- procedure under the null hypothesis assumption that Ho : δ = 0 (no change) and reported that this procedure may not preserve an δ - level of significance. As the result of the simulation study in [5], the observed α - values for n1 + n2 =20 and Ø =0.6 are: 0.077,0.178. and 0.259, compared to theoretical values of: 0.01,0.05 and 0.10 respectively. Also from this simulation study the observed (α - values) for n1 + n2 = 50 and Ø= 0.6 are: 0.034.0.112 and 0.185. These observed values are also greater than the theoretical values: 0.01, 0.05 and 0.10 respectively. Based on this preliminary and sketchy evidence, this study is being done to see whether this t-statistics can really control the type-1 error (α) for a wider category of Ø values: Ø= 0.0. 0.3, 0.6 and 0.9. and a wider choice of sample sizes. The same procedure in [5] will be used. |
| format | Article |
| id | my.uitm.ir-65589 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 1988 |
| publisher | Universiti Teknologi MARA, Pahang |
| record_format | eprints |
| spelling | my.uitm.ir-655892022-09-22T04:05:06Z https://ir.uitm.edu.my/id/eprint/65589/ Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat gading Mamat, Illias Mathematical statistics. Probabilities Matrix analytic methods Sequences (Mathematics) In order to test whether or not the intervention effect, δ which occurs between the pre-time series and the post-time series in an intervention time series model is different from zero, under appropriate assumptions. the t- statistics test suggested by Glass, Wilson, and Gottman (2) may be used. In this study. the first order autoregressive ARIMA (1,0,0,L,δ) intervention model. which contains the same pre- and post- intervention first-order autoregressive parameter Ø, is chosen in order to study the validity of the t-statistics. The variable Z will represent the series measured across n equally spaced units of time. This series is labelled as Z1,Z2-····,Zn. We shall assume the intervention effect occurs between times n1 and n1 + 1. where n1 < n. and where L is the level of the pre- intervention time series Z1,Z2 , Zn1' and (L+δ) is the level of post-intervention time series Znl+1, ,Zn. Zinkgraft and Wilson [5] simulated the performance of this t- procedure under the null hypothesis assumption that Ho : δ = 0 (no change) and reported that this procedure may not preserve an δ - level of significance. As the result of the simulation study in [5], the observed α - values for n1 + n2 =20 and Ø =0.6 are: 0.077,0.178. and 0.259, compared to theoretical values of: 0.01,0.05 and 0.10 respectively. Also from this simulation study the observed (α - values) for n1 + n2 = 50 and Ø= 0.6 are: 0.034.0.112 and 0.185. These observed values are also greater than the theoretical values: 0.01, 0.05 and 0.10 respectively. Based on this preliminary and sketchy evidence, this study is being done to see whether this t-statistics can really control the type-1 error (α) for a wider category of Ø values: Ø= 0.0. 0.3, 0.6 and 0.9. and a wider choice of sample sizes. The same procedure in [5] will be used. Universiti Teknologi MARA, Pahang 1988 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/65589/1/65589.PDF Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat. (1988) GADING Majalah Akademik ITM Cawangan Pahang <https://ir.uitm.edu.my/view/publication/GADING_Majalah_Akademik_ITM_Cawangan_Pahang/>, 1 (2): 6. pp. 36-56. |
| spellingShingle | Mathematical statistics. Probabilities Matrix analytic methods Sequences (Mathematics) Mamat, Illias Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title | Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title_full | Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title_fullStr | Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title_full_unstemmed | Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title_short | Simulation study of testing an intervention effect in arima (1,0,0,L,δ) model / Illias Mamat |
| title_sort | simulation study of testing an intervention effect in arima (1,0,0,l,δ) model / illias mamat |
| topic | Mathematical statistics. Probabilities Matrix analytic methods Sequences (Mathematics) |
| url | https://ir.uitm.edu.my/id/eprint/65589/1/65589.PDF https://ir.uitm.edu.my/id/eprint/65589/ |
| url_provider | http://ir.uitm.edu.my/ |