Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙特卡罗方法基本思想，基于不相称测定论，采用随机模拟的方法对药物不良反应监测数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙特卡罗方法基本思想，基于不相称性测定论，采用随机的方法对药物不良反应监测数据进行。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

法参照蒙特卡法基本思想，基于相称性测定论，采用随机模拟的法对药反应监测数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法蒙特卡罗方法基本思想，基于不相称性定论，采用随机模拟的方法对药物不良反应监进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙特卡罗方法基本思想，基于不测定论，采模拟的方法对药物不良反应监测数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

法参照蒙特卡法基本思想，基于相称性测定论，采用随机模拟的法对药反应监测数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙特卡罗方法基本思想，基于不相称，随机模拟的方法对药物不良反应监数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙罗方法基本思想，基于不相称性测定论，采用随机模拟的方法对药物不良反应监测数据进行模拟。

Results prove that worst-case or root-sum-square analyses are not adequate to predict probable performance accurately.A Monte Carlo analysis must be performed.

【文献摘要】A numerical analysis indicates that tolerance stackup effects in free-space optical interconnects are significant even for short systems containing few components.

Methods In accordance with Monte Carlo method and measures of disproportionality theory, simulate the adverse drug reaction surveillance data by the random mode.

方法参照蒙特卡罗方法基本思想，基于不相称性测定论，采用随机模拟的方法对药物不良应监测数据进行模拟。