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By constructing the covariance matrix using such non-linear kernel, the relationship between cells can be arbitrarily complex.
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From (8), we construct the covariance matrix C z for z.
We used all SNPs to construct the covariance matrix.
This is achieved by constructing a covariance matrix of phenotypes that represents the effects of genetic relatedness on phenotypes [ 16].
By constructing between-class covariance and within-class covariance, we attempt to minimize the between-class variance mainly caused by channel effect and to maximize the variance between speakers.
Therefore, it is more realistic to accommodate the departure from the infinitesimal model while constructing the variance-covariance matrix.
The largest errors are likely biases caused by unmodelled sources (Sabaka et al. 2015) which cannot be assessed using a formal model error covariance matrix, or by constructing models using the same technique from independent datasets.
The covariance function K and the noise covariance Σ ϵ depend on hyperparameters θ that can be estimated by maximizing the log marginal likelihood: (8) log (p (y | t, θ ) ) = − 1 2 y T [ K (t, t ) + Σ ϵ ] − 1 y − 1 2 log | K (t, t ) + Σ ϵ | − N 2 log (2 π ), where K (t, t ) denotes the covariance matrix constructed by evaluating the covariance function at points t.
An ellipsoidal parametric uncertainty set is constructed from the covariance matrix of the identified parameters.
DPLS can successfully deal with multicollinearity in the data by constructing a few (f) latent factors, T (m × f), which maximise the covariance between X and y [ 6].
The OLSE residuals are very useful to construct the variance and covariance matrix.
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