我们这篇文章主要研究了多重假设检验问题。
We mainly do some research on multiple hypothesis testing in this paper.
摘要：多重假设检验是限制局部空间关联模式分析的关键问题。
Multiple hypothesis testing is a key problem in spatial pattern detection using local statistics of spatial association.
基于错误发现率的多重假设检验校正方法在统计学等领域得到了广泛的重视，然而这些方法在空间分析领域的应用尚缺乏具体的验证。
Procedures controlling the false discovery rates (FDR) has been applied widely in domains such as statistics. However, the issue has received little attention in the geographical literature.
研究利用卡尔曼滤波器及多重故障假设检验方法来检测某发动机控制系统传感器硬、软故障，并实现故障传感器的输出重构。
According to Kalman filter and multiple-failure-hypothesis based testing, the sensor failures are detected, isolated and accommodated in turbofan engine control system.
研究利用卡尔曼滤波器及多重故障假设检验方法来检测某发动机控制系统传感器硬、软故障，并实现故障传感器的输出重构。
According to Kalman filter and multiple-failure-hypothesis based testing, the sensor failures are detected, isolated and accommodated in turbofan engine control system.
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