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The significance of the whole model is p = 0.000.
Therefore, the nonlinear dynamic model is P ′ t = Q μ.
The probability distribution of Gaussian background model is: p x = 1 2 π σ e x − μ 1 2 σ (1).
Therefore, the provider's profit using an on-demand model is: P od = C o − β E o ∑ i = 0 N t i.
Then the maximum likelihood estimate of the binomial model is p ̂ j = n j / N j, with log-likelihood: ∑ j = 1 J n j log p ̂ j + ( N j - n j ) log ( 1 - p ̂ j ).
The Hosmer and Lemeshow goodness-of-fit test for this model is p = 0.575.
Similar(48)
In [11], Chen et al. proved that computing the exact EIS under the LT model is #P-hard.
The criterion for inclusion in the model was p ≤ 0.05.
Criterion for inclusion of variables in the model was p < 0.05 and for exclusion p ≥ 0.10.
The predefined significance for inclusion in the next step of the regression model was p ≤ 0.10.
Overall statistical significance (F-test) for each model was p < 0.01.
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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