International Journal of Applied Mathematics and Theoretical Physics

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Statistical Change Point Analysis in Air Temperature and Rainfall Time Series for Cocoa Research Institute of Nigeria, Ibadan, Oyo State, Nigeria

Received: 27 August 2016    Accepted: 20 October 2016    Published: 13 December 2017
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Abstract

In this work, a cumsum approach is used to detect change-point in mean of an independent normal random variables. A multiple shift in the mean level was considered and show how such a problem can be straightforwardly addressed through the cumsum approach. Data gotten from Cocoa Research Institute of Nigeria were used and from the result of the analysis, a single change point was detected in the amount of rainfall and a multiple change point was detected in the amount of minimum temperature and no change point was detected in the amount of maximum temperature.

DOI 10.11648/j.ijamtp.20170304.13
Published in International Journal of Applied Mathematics and Theoretical Physics (Volume 3, Issue 4, October 2017)
Page(s) 92-96
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Change Point, Cumsum

References
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[4] Nebojsa Nakicenovic, Joseph Alcamo, Gerald Davis, Bert de Vries, Joergen Fenhann, Stuart Gaffin, Kenneth Gregory, Arnulf Grübler, Tae Yong Jung, Tom Kram, Emilio Lebre La Rovere, Laurie Michaelis, Shunsuke Mori, Tsuneyuki Morita, William Pepper, Hugh Pitcher, Lynn Price, Keywan Riahi, Alexander Roehrl, Hans-Holger Rogner, Alexei Sankovski, Michael Schlesinger, Priyadarshi Shukla, Steven Smith, Robert Swart, Sascha van Rooijen, Nadejda Victor and Zhou Dadi (2000), Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change. Technical report, Cambridge University Press, Cambridge, UK, 2000.
[5] C. Serra, A. Burgueno, and X. Lana (2014), Analysis of maximum and minimum daily temperatures recorded at fabran observatory in the period 1971-1998. International Journal of Climatology, 21: 617(636).
[6] T. Szentimrey, J. Salinger, E. J. Førland, I. Hanssen-Bauer, H. Alexandersson, P. Jones and D. Parker (1998), Homogeneity adjustments of in situ atmospheric climate data: A review. International journal of climatology, 18: 1493(1517).
[7] T. R. Karl and C. N. Williams (1987), An approach to adjusting climatological time series for discontinuous inhomogeneities. Journal of Climate & Applied Meteorology, 26: 1744(1763.
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[9] Shrestha AB, Wake CP, Dibb JE, Mayewski PA (2000) Precipitation fluctuations in the Nepal Himalaya and its vicinity and relationship with some large scale climatological parameters. International Journal of Climatology 20: 317-327.
Author Information
  • Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria

  • Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria

  • Department of Statistics, University of Ilorin, Ilorin, Nigeria

  • Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria

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  • APA Style

    N. P. Dibal, M. Mustapha, Adegoke T. M., A. M. Yahaya. (2017). Statistical Change Point Analysis in Air Temperature and Rainfall Time Series for Cocoa Research Institute of Nigeria, Ibadan, Oyo State, Nigeria. International Journal of Applied Mathematics and Theoretical Physics, 3(4), 92-96. https://doi.org/10.11648/j.ijamtp.20170304.13

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    ACS Style

    N. P. Dibal; M. Mustapha; Adegoke T. M.; A. M. Yahaya. Statistical Change Point Analysis in Air Temperature and Rainfall Time Series for Cocoa Research Institute of Nigeria, Ibadan, Oyo State, Nigeria. Int. J. Appl. Math. Theor. Phys. 2017, 3(4), 92-96. doi: 10.11648/j.ijamtp.20170304.13

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    AMA Style

    N. P. Dibal, M. Mustapha, Adegoke T. M., A. M. Yahaya. Statistical Change Point Analysis in Air Temperature and Rainfall Time Series for Cocoa Research Institute of Nigeria, Ibadan, Oyo State, Nigeria. Int J Appl Math Theor Phys. 2017;3(4):92-96. doi: 10.11648/j.ijamtp.20170304.13

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  • @article{10.11648/j.ijamtp.20170304.13,
      author = {N. P. Dibal and M. Mustapha and Adegoke T. M. and A. M. Yahaya},
      title = {Statistical Change Point Analysis in Air Temperature and Rainfall Time Series for Cocoa Research Institute of Nigeria, Ibadan, Oyo State, Nigeria},
      journal = {International Journal of Applied Mathematics and Theoretical Physics},
      volume = {3},
      number = {4},
      pages = {92-96},
      doi = {10.11648/j.ijamtp.20170304.13},
      url = {https://doi.org/10.11648/j.ijamtp.20170304.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijamtp.20170304.13},
      abstract = {In this work, a cumsum approach is used to detect change-point in mean of an independent normal random variables. A multiple shift in the mean level was considered and show how such a problem can be straightforwardly addressed through the cumsum approach. Data gotten from Cocoa Research Institute of Nigeria were used and from the result of the analysis, a single change point was detected in the amount of rainfall and a multiple change point was detected in the amount of minimum temperature and no change point was detected in the amount of maximum temperature.},
     year = {2017}
    }
    

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    AB  - In this work, a cumsum approach is used to detect change-point in mean of an independent normal random variables. A multiple shift in the mean level was considered and show how such a problem can be straightforwardly addressed through the cumsum approach. Data gotten from Cocoa Research Institute of Nigeria were used and from the result of the analysis, a single change point was detected in the amount of rainfall and a multiple change point was detected in the amount of minimum temperature and no change point was detected in the amount of maximum temperature.
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