• Title/Summary/Keyword: An unstable AR(1) model

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Limiting Distributions of Trimmed Least Squares Estimators in Unstable AR(1) Models

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.151-165
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    • 1999
  • This paper considers the trimmed least squares estimator of the autoregression parameter in the unstable AR(1) model: X\ulcorner=ØX\ulcorner+$\varepsilon$\ulcorner, where $\varepsilon$\ulcorner are iid random variables with mean 0 and variance $\sigma$$^2$> 0, and Ø is the real number with │Ø│=1. The trimmed least squares estimator for Ø is defined in analogy of that of Welsh(1987). The limiting distribution of the trimmed least squares estimator is derived under certain regularity conditions.

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Behavioral Change of Workers who completed Experiential Safety Training (체험식 안전교육 이수 근로자의 행동 변화 연구)

  • Choonhwan, Cho
    • Journal of the Society of Disaster Information
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    • v.19 no.1
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    • pp.161-172
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    • 2023
  • Safety education delivered to construction workers in a lecture manner has limitations in concentration and immersion, so delivery power and interest are low. In order to improve unstable behavior through education and prevent safety accidents, it is necessary to change the paradigm to hands-on education. Purpose: Experiential safety education aims to contribute to preventing accidents for construction workers by quickly recognizing risks, improving emergency response skills, and verifying the effectiveness of pre- and post-learning. Method: Based on a survey of workers who experienced the same work environment as the actual construction site, an opinion survey on the pre- and post-safety experience education and a variable measurement tool were planned, and a research hypothesis was established. Results: The Bayesian theory and MC simulation analysis were used to analyze the structural equation model, and the change in construction worker behavior was confirmed through the intended safety (A), non-experiential education in the sub-area of anxiety (B), average, standard deviation, and minimum and maximum values. Conclusion: The effect of education and industrial accidents are reduced only when construction workers are motivated to participate.