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Abstract

First order Space-Time Autoregressive model is one of the models which involves location and time. STAR(1;1) model stationary can be used to forecast future observation at a location based on one previous time of its own location and the spatial neighborhood. STAR(1;1) model on petroleum productivity data in Balongan, Indramayu, West Java with eigenvalue less than 1. It indicates that STAR (1;1) model on petroleum productivity data in Balongan, Indramayu, West Java meets the stationary requirement

Keywords

autoregressive petroleum data STAR first order

Article Details

How to Cite
1.
Joebaedi K, Parmikanti K, Badrulfalah B. First Order Space Time Autoregressive Stationary Model on Petroleum Data. EKSAKTA [Internet]. 2018Oct.30 [cited 2024Apr.19];19(2):62-9. Available from: https://eksakta.ppj.unp.ac.id/index.php/eksakta/article/view/152

References

    [1] Jacob BG, Morris JA, Caamano EX, Griffith DA, Novak RJ. 2011. Geomapping generalized eigenvalue frequency distributions for predicting prolific Aedes albopictus and Culex quinquefasciatus habitats based on spatiotemporal field-sampled count data. Acta tropica 117:61-8
    [2] Jin X, Carlin BP. 2005. Multivariate parametric spatiotemporal models for county level breast cancer survival data. Lifetime data analysis 11:5-27
    [3] Li W, Ma X, Zhu Y, Yang J, Hou C. 2008. Detection in reverberation using space time adaptive prewhiteners. The Journal of the Acoustical Society of America 124:EL236-42
    [4] Tang W, Malanson GP, Entwisle B. 2009. Simulated village locations in Thailand: A multi-scale model including a neural network approach. Landscape ecology 24:557-75
    [5] Shim J, Hwang C. 2018. Kernel-based geographically and temporally weighted autoregressive model for house price estimation. PloS one 13:e0205063
    [6] Garthe RC, Sullivan TN, Farrell A. 2018. Dating violence perpetration and perceived parental support for fighting and nonviolent responses to conflict: An autoregressive cross-lagged model. Journal of adolescence 68:221-31
    [7] Yang Y, Arias G. 2018. Identification of hinging hyperplane autoregressive exogenous model using efficient mixed-integer programming. ISA transactions 81:18-31
    [8] Fu TC, Chen CC, Chang CM, Chang HH, Chu HT. 2018. Analysis of Exercise-Induced Periodic Breathing Using an Autoregressive Model and the Hilbert-Huang Transform. Computational and mathematical methods in medicine 2018:4860204
    [9] Ebhuoma O, Gebreslasie M, Magubane L. 2018. A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict monthly malaria cases in KwaZulu-Natal, South Africa. South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde 108:573-8
    [10] Wen Y, Shen X, Lu Q. 2018. Genetic risk prediction using a spatial autoregressive model with adaptive lasso. Statistics in medicine 37:3764-75
    [11] Bringmann LF, Ferrer E, Hamaker EL, Borsboom D, Tuerlinckx F. 2018. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model. Multivariate behavioral research 53:293-314
    [12] Box, G.E.P and Jenkins, G. M. 1976. Time Series Analysis, Forecasting and Control. San Fransisco: Holden-Day, Inc.
    [13] Ruchjana, B. N. 2002. The Stationary of The Space Time Autoregressive Model. Majalah Ilmiah Himpunan Matematika Indonesia (MIHMI), Vol. 8 No. 2, ISSN: 0854-1380, hal. 151-159.
    [14] Ruchjana, B. N, 2002. Suatu Model Generalisasi Space Time Autoregresi (GSTAR) Orde1 dan Aplikasinya pada Data Produksi Minyak Bumi. Disertasi Program S3 Matematika ITB. Indah Dipublikasikan. Bandung; ITB
    [15] Pfeifer, P.E., 1979. Spasial Dynamic Modeling, unpublished Ph.D Dissertation, Georgia Institute of Technology, Georgia.
    [16] Hannan,E.j, 1970. Multiple Time Series. John Wiley and Sons. Inc. New York
    [17] Wei, W. W. S, 1994, Time Series Analysis, Addison Wesley Publishing Company, Inc.

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