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逆高斯模型下双因素实验的分析AI 解读

This article treats the analysis of factorial experiments under an inverse Gaussian distribution for the failure times. A reciprocal-linear model for the factor effects is motivated from the context of the underlying Wiener process. Explicit solutions to the likelihood equations are derived, and important properties such as strong consistency and limiting normality are established. A least squares approach using the reciprocals of the sample cell means is also studied and…

逆高斯模型下的双因素实验分析AI 解读

This article treats the analysis of factorial experiments under an inverse Gaussian distribution for the failure times. A reciprocal-linear model for the factor effects is motivated from the context of the underlying Wiener process. Explicit solutions to the likelihood equations are derived, and important properties such as strong consistency and limiting normality are established. A least squares approach using the reciprocals of the sample cell means is also studied and…