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By expressing the model in a Bayesian framework, different statistical methods can be implemented in GPR models.
By expressing the model in a Bayesian framework, the authors extend GPR applications beyond spatial interpolation to regression problems.
To this end, we have used transgenic mice expressing the model autoantigen ovalbumin in pancreatic islets and transgenic ovalbumin-specific CD4 and CD8 T cells.
Expressing the model in this way is useful since the problem of estimating g may now be regarded as that of fitting a curve through the sample means Y ¯ ( x i ).
However, due to the sampled recording of measurements, we are interested in expressing the model in the form of a discrete state-space, {boldsymbol{x}}_{k} = f_{k} ({boldsymbol{x}}_{k-1}) + boldsymbol{nu}_{k} (5).
In expressing the model we follow the notation used by Muthén and Masyn [27].
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Firstly, we express the model's surface by the wavelet decomposition expressions and obtain a reconstructed surface and then validate its accuracy.
In contrast to Figure 4B, in which PI4KIII β was ectopically expressed, the model suggests that CERT still increases after 24 hours of vector expression.
In Section 3 we express the model problem as an inequality and Laplacian constrained variational optimization problem.
All transformants expressed the model membrane protein, while the resulting plasmid from each clone contained the designed mutations only.
Thus, we express the model of a new speaker as M new = U mixture W new U dim T + M ¯. (14).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com