Log in

Relevant bibliographies by topics / Nonseasonal ARIMA

Contents

Journal articles

Academic literature on the topic 'Nonseasonal ARIMA'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Nonseasonal ARIMA.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Nonseasonal ARIMA"

1

Peiris, M. Shelton, and N. Singh. "Predictors for Seasonal and Nonseasonal Fractionally Integrated ARIMA Models." Biometrical Journal 38, no. 6 (1996): 741–52. http://dx.doi.org/10.1002/bimj.4710380615.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Harrison, Etuk Ette, Moffat Imoh Udo, and Chims Benjamin Ele. "Modelling Monthly Rainfall Data of Port Harcourt, Nigeria by Seasonal Box-Jenkins Methods." International Journal of Sciences Volume 2, no. 2013-07 (2013): 60–67. https://doi.org/10.5281/zenodo.3348244.

Full text

Abstract:

Brief review of literature of the well documented seasonal Box-Jenkins modelling is done. Rainfall is a seasonal phenomenon the world over. For illustrative purposes, monthly rainfall as measured in Port Harcourt, Nigeria, is modelled by a (5, 1, 0)x(0, 1, 1)12 seasonal ARIMA model. The time-plot shows no noticeable trend. The known and expected seasonality is clear from the plot. Seasonal (i.e. 12-point) differencing of the data is done, then a nonseasonal differencing is done of the seasonal differences. The correlogam of the resultant series reveals the expected 12-monthly seasonality, and

APA, Harvard, Vancouver, ISO, and other styles

3

Bell, William R. "Unit Root Properties of Seasonal Adjustment and Related Filters: Special Cases." Journal of Official Statistics 33, no. 1 (2017): 1–14. http://dx.doi.org/10.1515/jos-2017-0001.

Full text

Abstract:

Abstract Bell (2012) catalogued unit root factors contained in linear filters used in seasonal adjustment (model-based or from the X-11 method) but noted that, for model-based seasonal adjustment, special cases could arise where filters could contain more unit root factors than was indicated by the general results. This article reviews some special cases that occur with canonical ARIMA model based adjustment in which, with some commonly used ARIMA models, the symmetric seasonal filters contain two extra nonseasonal differences (i.e., they include an extra (1 - B)(1 - F)). This increases by two

APA, Harvard, Vancouver, ISO, and other styles

4

Etuk, Ette Harrison. "A Multiplicative Seasonal Arima Model for Nigerian Unemployment Rates." Bulletin of Society for Mathematical Services and Standards 3 (September 2012): 46–53. http://dx.doi.org/10.18052/www.scipress.com/bsmass.3.46.

Full text

Abstract:

Time series analysis of Nigerian Unemployment Rates is done. The data used is monthly from 1948 to 2008. The time plot reveals a slightly positive trend with no clear seasonality. A multiplicative seasonal model is suggestive given seasonality that typically tends to increase with time. Seasonal differencing once produced a series with no trend nor discernible stationarity. A non-seasonal differencing of the seasonal differences yielded a series with no trend but with a correlogram revealing stationarity of order 12, a nonseasonal autoregressive component of order 3 and a seasonal moving avera

APA, Harvard, Vancouver, ISO, and other styles

5

Senyefia, Bosson-Amedenu. "Nonseasonal ARIMA Modeling and Forecasting of Malaria Cases in Children under Five in Edum Banso Sub-district of Ghana." Asian Research Journal of Mathematics 4, no. 3 (2017): 1–11. https://doi.org/10.9734/ARJOM/2017/33374.

Full text

Abstract:

Approximately sixty-nine percent of deaths globally resulting from malaria infection occur in children under five years of age [1]. National control and prevention strategies will be greatly enhanced through better ability to forecast future trends in the disease incidence. This study sought to develop a five year forecasting model for malaria incidence among children under the age of five in the Edum Banso sub- district of Ghana. A secondary monthly malaria incidence record data spanning the period of 2008-2013 was used to develop the model formulated. The Box and Jenkins ARIMA methodology wa

APA, Harvard, Vancouver, ISO, and other styles

6

Tran, Thai Thanh, Luong Duc Thien, Ngo Xuan Quang, and Lam Van Tan. "Forecasting of saline intrusion in Ham Luong river, Ben Tre province (Southern Vietnam) using Box-Jenkins ARIMA models." Science and Technology Development Journal 23, no. 1 (2020): 446–53. http://dx.doi.org/10.32508/stdj.v23i1.1747.

Full text

Abstract:

Introduction: Ham Luong River is a branch of Mekong River located in Ben Tre Province, which has played a crucial role in supporting livelihoods of local residents and the province's economic development. However, the saline intrusion has been expanding in Ham Luong River, which seriously affects the productive agriculture, aquaculture, and further causes tremendous difficulties for local people's lives. Thus, it is crucial to have research for forecast the saline intrusion in Ham Luong River. Our aim was to develop mathematical models in order to forecast the saline intrusion in Ham Luong Riv

APA, Harvard, Vancouver, ISO, and other styles

7

Hoover, Stephen, Eric Jackson, David Paul, Robert Locke, and Muge Capan. "Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit." Applied Clinical Informatics 07, no. 02 (2016): 275–89. http://dx.doi.org/10.4338/aci-2015-09-ra-0127.

Full text

Abstract:

SummaryAccurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations.Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasti

APA, Harvard, Vancouver, ISO, and other styles

8

Rao, Lei, and Larry Owen. "Validation of High-Fidelity Traffic Simulation Models." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (2000): 69–78. http://dx.doi.org/10.3141/1710-08.

Full text

Abstract:

A multistage validation framework that accounts for the realistic nature of traffic simulation output data is proposed. The framework consists of conceptual validation and operational validation. The operational validation comprises a qualitative approach, which involves static and animated Turing tests, and a quantitative approach, which involves three levels of statistical tests. Particularly in the third-level statistical test, the autocorrelation and nonstationary nature of traffic simulation output data is emphasized, its implications on validation methods are explored, and a univariate n

APA, Harvard, Vancouver, ISO, and other styles

9

Atiqah Rochin Demong, Nur, Jie Lu, and Farookh Khadeer Hussain. "An Adaptive Personalized Property Investment Risk Analysis Method Based on Data-Driven Approach." International Journal of Information Technology & Decision Making 20, no. 02 (2021): 671–706. http://dx.doi.org/10.1142/s0219622021500115.

Full text

Abstract:

Risk assessment analysis for investment decisions largely depends on expert judgment using traditional approaches and is lacking in considering investors’ different preferences and limitations. This paper proposes an adaptive personalized property investment risk analysis (APPIRA) method to identify the property investment determinants using a data-driven and personalized approach to weight the risk factors using the multicriteria decision model for optimal solutions. Result for predictive modeling using value prediction technique that measures the median house price depicts that the best meth

APA, Harvard, Vancouver, ISO, and other styles

10

Bosson-Amedenu, Senyefia. "Nonseasonal ARIMA Modeling and Forecasting of Malaria Cases in Children under Five in Edum Banso Sub-district of Ghana." Asian Research Journal of Mathematics 4, no. 3 (2017): 1–11. http://dx.doi.org/10.9734/arjom/2017/33374.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!