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That is, if we take dead force to be equal to be the derivative of the body's velocity with respect to time multiplied by its mass, i.e. dead force = mass (dv/dt).
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The components are forced to be equal to minimize the sum, so the large samples are pushed to a specific level, whereas the smaller ones become larger.
In the steady state, the two normalized variables will be forced to be equal, thus the error would be zero [34].
We have also statistically tested this by estimating a constrained specification by which all slope coefficients are forced to be equal.
In the above equations, (varepsilon _i^{(s)}) denotes the total selling energy of MG i, which is forced to be equal to all the energy bought by other MGs from MG i.
When raw data were obtained from twin studies, we attempted to fit variance components models to change scores in order to estimate the rMZ and rDZ simultaneously and formally compare models in which these two parameters were forced to be equal with models in which they were allowed to differ.
This approach consists in comparing a 'free' model in which all paths are allowed to vary between two conditions, to a 'restricted' model in which the tested path is forced to be equal across conditions.
Next, the factor loading estimates were forced to be equal across both modes.
However, because the a = c restriction is still in place, the variation is forced to be equal across groups.
Hence, when the number of sequences is forced to be equal, it does not inflate the estimation of substitution rates.
We note that in model (A1) the within- and between group coefficients are forced to be equal, which is an unrealistic assumption for many practical applications.
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CEO of Professional Science Editing for Scientists @ prosciediting.com