Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors
With a view to providing a tool to accurately model time series processes which may be corrupted with errors such as measurement, round-off and data aggregation, this study developed an integrated moving average (IMA) model with a transition matrix for the errors resulting in a convex combination of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2019-01-01
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| Series: | Statistical Theory and Related Fields |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24754269.2019.1598833 |
| _version_ | 1797677068793675776 |
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| author | S. A. Komolafe T. O. Obilade I. O. Ayodeji A. R. Babalola |
| author_facet | S. A. Komolafe T. O. Obilade I. O. Ayodeji A. R. Babalola |
| author_sort | S. A. Komolafe |
| collection | DOAJ |
| description | With a view to providing a tool to accurately model time series processes which may be corrupted with errors such as measurement, round-off and data aggregation, this study developed an integrated moving average (IMA) model with a transition matrix for the errors resulting in a convex combination of two ARMA errors. Datasets on interest rates in the United States and Nigeria were used to demonstrate the application of the formulated model. Basic tools such as the autocovariance function, maximum likelihood method, Newton–Raphson iterative method and Kolmogorov–Smirnov test statistic were employed to examine and fit the formulated specification to data. Test results showed that the proposed model provided a generalisation and a more flexible specification than the existing models of AR error and ARMA error in fitting time series processes in the presence of errors. |
| first_indexed | 2024-03-11T22:39:41Z |
| format | Article |
| id | doaj.art-44a105852ebc46cb93b3982be641ddbf |
| institution | Directory Open Access Journal |
| issn | 2475-4269 2475-4277 |
| language | English |
| last_indexed | 2024-03-11T22:39:41Z |
| publishDate | 2019-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Statistical Theory and Related Fields |
| spelling | doaj.art-44a105852ebc46cb93b3982be641ddbf2023-09-22T09:19:45ZengTaylor & Francis GroupStatistical Theory and Related Fields2475-42692475-42772019-01-0131485810.1080/24754269.2019.15988331598833Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errorsS. A. Komolafe0T. O. Obilade1I. O. Ayodeji2A. R. Babalola3Obafemi Awolowo UniversityObafemi Awolowo UniversityObafemi Awolowo UniversityObafemi Awolowo UniversityWith a view to providing a tool to accurately model time series processes which may be corrupted with errors such as measurement, round-off and data aggregation, this study developed an integrated moving average (IMA) model with a transition matrix for the errors resulting in a convex combination of two ARMA errors. Datasets on interest rates in the United States and Nigeria were used to demonstrate the application of the formulated model. Basic tools such as the autocovariance function, maximum likelihood method, Newton–Raphson iterative method and Kolmogorov–Smirnov test statistic were employed to examine and fit the formulated specification to data. Test results showed that the proposed model provided a generalisation and a more flexible specification than the existing models of AR error and ARMA error in fitting time series processes in the presence of errors.http://dx.doi.org/10.1080/24754269.2019.1598833structural relationshipmeasurement errorcorrelated errorsautocovariance function |
| spellingShingle | S. A. Komolafe T. O. Obilade I. O. Ayodeji A. R. Babalola Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors Statistical Theory and Related Fields structural relationship measurement error correlated errors autocovariance function |
| title | Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors |
| title_full | Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors |
| title_fullStr | Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors |
| title_full_unstemmed | Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors |
| title_short | Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors |
| title_sort | development of a first order integrated moving average model corrupted with a markov modulated convex combination of autoregressive moving average errors |
| topic | structural relationship measurement error correlated errors autocovariance function |
| url | http://dx.doi.org/10.1080/24754269.2019.1598833 |
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