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Discover LudwigThe phrase "under model" is not correct and does not convey a clear meaning in written English.
It may be intended to refer to a specific model or framework, but without additional context, it is unclear when to use it. Example: "The results were analyzed under model conditions, but the specifics were not provided."
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Therefore, all further analyses will be done under model II.
Consequently, the classical ITC methods operates under model mismatch.
Under model (1.1) and the loss function (1.2), if is estimable, then if and only if.
DMU 6 under model (2.2) performs with efficiency (g_6^ = frac{3}{4}).
Double cross-validation reliably and unbiasedly estimates prediction errors under model uncertainty for regression models.
Under Model 1, the validation sample is a simple random sample with probability π i =0.4.
Under model (1.1) with the loss function (1.2), suppose is an estimator of, one has (2.1).
Reliable estimation of prediction errors is challenging – especially under model uncertainty – and requires independent test objects.
Under model (1.1) and the loss function (1.2), if is inestimable, then if and only if.
The adaptive backstepping controller provides system stability under model uncertainty, and achieves the desired servo performance.
Simulation results under model uncertainties show the effectiveness of the proposed adaptive control concept.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com