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The mixed model we used is described as follows: where Y ij is pulse pressure of subject i at time j, β0 is a fixed intercept, β1- β5 are fixed coefficients representing the estimated effects of each following term, u i is the random intercept that reflects unexplained subject to subject heterogeneity that induces correlation among observations from the same subject, and ε ij is a random error.
The fixed predictor uses the fixed coefficients.
Hence, it is a useful technique for implementing FIR Filters with fixed coefficients.
The performance of an L-estimator depends on its weights which are some fixed coefficients.
Here a1 and a2 are fixed coefficients and U is a so-called error term, which we may take to represent the other causal influences on Y besides X1 and X2.
In this connection, we have already mentioned the Schur-Cohn criterion, which can be applied to any polynomial Q with concrete (fixed) coefficients and order.
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The fixed coefficient λ is extended to the case of a sequence ({lambda_{n}}).
(ii) The fixed coefficient γ is extended to the case of a sequence ({gamma_{n}}).
However, the use of the derivative smoothness constraints with a fixed coefficient does not warrant uniform imposition of these constraints at every iteration.
(4 where ( {C}_j^{SL} ) and ( {C}_j^{RL} ) respectively denote the fixed coefficient between active load and reactive load of shapeable load j and removable load j.
For the non-energy industry sectors, THERESIA assumes fixed coefficient input relationship between intermediate inputs excluding energy inputs and value-added plus secondary energy input.
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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