Separating the effect of one link is analogous to ICM, resulting in the following sampling equation: (4) Separating the effect of one node and its expression profile in turn results in the following sampling equation: (5) where posterior covariance matrix S is (6) and posterior mean A is (7) The notation A' in (5) denotes that A is computed without the effect of the left-out node data.
Matrix of covariances, correlation coefficients, and posterior probabilities for maximal male SVL, range size estimates and synonymous substitution rate Ds obtained with CoEvol.
Our simulation results favor Bayesian design criteria based on the generalized Fisher information matrix and on the expected posterior covariance matrix.
In this work, the cameras in the VSN use the extended information filter (EIF) as the local filter and calculate the expected information gain (EIG) in the form of a logarithmic ratio of the expected and posterior information matrices.
Anterior and posterior thorax images (matrix 256 × 256) were acquired for 300 seconds at 6 h and 600 seconds at 24 h.
Acquisition parameters are as follows: 3D T1 fast spoiled gradient echo sequence; repetition time (TR) = 10.8 ms; echo time (TE) = 4.8 ms; slice orientation, parallel with the anterior and posterior commissure line; matrix = 256 × 256; field of view = 256 mm × 256 mm; slice thickness = 1 mm; no gap; and 140 continuous slices were acquired, covering the whole brain.
Given that σ, the standard deviation of the Gaussian observation error ε, is known and the prior distribution over the parameters is a Gaussian with standard deviation ξ, the mean and covariance matrix of the posterior distribution can be computed analytically (see Additional file 1: section S4).
We compare designs based on the Fisher information matrix with designs based on the generalized Fisher information matrix, the expected posterior covariance matrix, and the expected gain in Shannon information.
The estimated prior transition matrix and the average of the posterior transition matrices for the time homogeneous model are hat{mathbf{P}}=left(begin{array}{ll} 0.776 &0.224 0.068&0.932 end{array}right), left(bar{mathbf{P}}|Delta I_{it}right)=left(begin{array}{ll} 0.573 &0.427 0.174&0.826 end{array}right).
We compared the total time and the real-time factor of i-supervector and i-vector systems at four different stages, namely, loading matrix estimation, posterior extraction, PLDA modeling, and PLDA scoring.
