首页> 外文OA文献 >Development of a Markov Model for Forecasting Continuation Rates for Enlisted Prior Service and Non-Prior Service Personnel in the Selective Marine Corps Reserve (SMCR)
【2h】

Development of a Markov Model for Forecasting Continuation Rates for Enlisted Prior Service and Non-Prior Service Personnel in the Selective Marine Corps Reserve (SMCR)

机译:马尔可夫模型的开发,用于预测选择性海军陆战队预备役(SMCR)中应征入伍的在职人员和非在职人员的续任率

摘要

The purpose of this thesis is to develop a Markov model to determine the continuation rates for Prior Service and Non-Prior Service enlisted population in the Selected Marine Corps Reserve (SMCR). Determining the end strength for these populations is necessary for reserve manpower planners to balance the force structure to minimize personnel overage or underages that impact training and labor costs, as well as career progression. The results of model validation indicate that models based on annual aggregate monthly transition rates fails the stationarity assumption required of Markov models. These results suggest that the attrition behaviors are seasonal for both enlisted populations leading to numerous states being non stationary in part due to their correlation with seasonality. We recommend developing and employing models with unique transition rates for each month.
机译:本文的目的是建立一个马尔可夫模型,以确定选定海军陆战队预备役(SMCR)中在役和非在役士兵的续居率。确定这些人口的最终兵力对于储备人力计划者来说是必要的,以平衡部队结构,以最大程度地减少影响培训和劳动力成本以及职业发展的人员过剩或不足。模型验证的结果表明,基于年度总月度过渡率的模型无法满足马尔可夫模型所要求的平稳性假设。这些结果表明,两个入伍人群的消耗行为都是季节性的,这导致许多州的不稳定是部分由于其与季节的相关性。我们建议开发和使用每个月具有唯一转换率的模型。

著录项

  • 作者

    Erhardt Bruce J. Jr.;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号