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微分方程参数估计：广义平滑方法AI 解读

Summary We propose a new method for estimating parameters in models that are defined by a system of non-linear differential equations. Such equations represent changes in system outputs by linking the behaviour of derivatives of a process to the behaviour of the process itself. Current methods for estimating parameters in differential equations from noisy data are computationally intensive and often poorly suited to the realization of statistical objectives such as inference…

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线性回归中斜率、截距与尺度的若干稳健估计比较AI 解读

Three classes of M estimates for robust linear regression are investigated for various contaminated normal distributions, sample sizes, and distributions of the independent variable. These are the Lp estimates, the amt estimate, and a new class of estimates (Ea ) with bounded influence function. It is found that the Ea class consistently outperforms the Lp class, performs about as well as the amt estimate, and solutions for Ea estimates can be obtained rapidly and reliably.…