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In other words, each generated forecasting model h with error larger than 1/2 is ignored.
Same as Fig. 2 but for Model H with various ac.
Since the grain velocities at a < 10−5 cm drops below 20 km s−1 for Model A (Fig. 6), Model H with ac = 10−5 cm produce a more similar grain size distribution to Model A than Model H with ac = 10−6 cm.
with ({sf H}_{h} = left [{sf A}_{h}^{T}{sf C}_{h}^{-1} {sf A}_{h} + {sf R}_{h}^{-1}right ]^{-1}) the covariance matrix defining the a posteriori error statistics of the model h (with similar definitions for v).
We consider a model H with a given set of freely varying parameters that defines a vector ; i.e. each component of θ is a parameter of the model.
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Temporally filtered estimates of the homography are obtained by modeling H with a zero-order Kalman filter whose state vector is composed of the elements H ij of the homography matrix.
Using running time polynomial in (1/delta), n, (1/gamma) and s, boosting algorithm outputs an accurate forecast model (H) that with probability at least (1 - delta) is (gamma) -close to c under D. As defined the class h required having a prediction error slightly better than 1/2 with respect to the distribution D on which it is trained.
b To include the channel estimation error in the proposed model, H can be replaced with H + N in Equation 9, where N denotes the channel estimation error matrix.
On the contrary, the model H is in better agreement with the mean model at larger SH orders but agrees less well at low SH orders.
The method homogenises the variance of hybridisation intensities from a set of samples by transformation of the data with the model h(x) = arcsinh (a + bx).
In the multivariable Cox model, H-statins were associated with significantly improved PFS compared with no statin (hazard ratio=0.49; 95% confidence interval=0.28 0.84; P<0.01); OS and DSS P-values were 0.80 and 0.85, respectively.
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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