Time-series analysis of industrial accident data

Andris Freivalds; Alison B. Johnson

doi:10.1016/0376-6349(90)90020-V

Time-series analysis of industrial accident data

Andris Freivalds, Alison B. Johnson

Marcus Department of Industrial and Manufacturing Engineering

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Freivalds, A. and Johnson, A.B., 1990. Time-series analysis of industrial accident data. Journal of Occupational Accidents, 13: 179-193. Considering the cyclical nature of accident and injury data, it is reasonable to consider the use of time-series analysis for modeling these data. One approach involved fitting a Box-Jenkins, auto-regressive, moving-average model to the data and using the model to forecast future values. A second approach utilized sine or cosine models to fit the cyclical pattern. A comparison of the two models, for a set of injury data in a glass manufacturing facility, indicated a clear superiority of the Box-Jenkins approach; not only for fitting a seasonal cycle, but also for accommodating monthly trends.

Original language	English (US)
Pages (from-to)	179-193
Number of pages	15
Journal	Journal of Occupational Accidents
Volume	13
Issue number	3
DOIs	https://doi.org/10.1016/0376-6349(90)90020-V
State	Published - Oct 1990

All Science Journal Classification (ASJC) codes

Public Health, Environmental and Occupational Health
Safety Research

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/0376-6349(90)90020-V

Cite this

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title = "Time-series analysis of industrial accident data",

abstract = "Freivalds, A. and Johnson, A.B., 1990. Time-series analysis of industrial accident data. Journal of Occupational Accidents, 13: 179-193. Considering the cyclical nature of accident and injury data, it is reasonable to consider the use of time-series analysis for modeling these data. One approach involved fitting a Box-Jenkins, auto-regressive, moving-average model to the data and using the model to forecast future values. A second approach utilized sine or cosine models to fit the cyclical pattern. A comparison of the two models, for a set of injury data in a glass manufacturing facility, indicated a clear superiority of the Box-Jenkins approach; not only for fitting a seasonal cycle, but also for accommodating monthly trends.",

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AB - Freivalds, A. and Johnson, A.B., 1990. Time-series analysis of industrial accident data. Journal of Occupational Accidents, 13: 179-193. Considering the cyclical nature of accident and injury data, it is reasonable to consider the use of time-series analysis for modeling these data. One approach involved fitting a Box-Jenkins, auto-regressive, moving-average model to the data and using the model to forecast future values. A second approach utilized sine or cosine models to fit the cyclical pattern. A comparison of the two models, for a set of injury data in a glass manufacturing facility, indicated a clear superiority of the Box-Jenkins approach; not only for fitting a seasonal cycle, but also for accommodating monthly trends.

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Time-series analysis of industrial accident data

Abstract

All Science Journal Classification (ASJC) codes

UN SDGs

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