Sentence examples for matrix of posterior from inspiring English sources

The algorithm was implemented in the software POPS, and is described in more details in Appendix A. For each subset of covariates, we additionally computed a matrix of posterior predictive membership probabilities using a Monte Carlo method.

BEAGLE outputs an individual × SNP matrix of posterior probabilities that each SNP is part of an autozygous segment.

One of the outputs from a run of the Markov chain sampler is an n × K matrix of posterior assignment probabilities.

The multivariate analysis allowed us to estimate a full matrix of posterior distributions of (co variance for all the traits together in the model, and to take into account that associated traits may not evolve independently of each other.

We used deviance information criterion (DIC) values and stabilization of the Q-matrix of posterior probabilities to determine the optimal number of clusters (i.e. Kmax) for the data.

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).

In our method, the convergence rate of the DAAEM algorithm for mixture model is first derived from Jacobian matrix of the posterior probabilities.

The result of the MCMC simulation is a sample of network structures which leads to a matrix of marginal posterior probabilities associated with the edges in a network.

In a random-walk MH algorithm (Robert et al. 2004) we used a multivariate normal proposal distribution with expectation equal to the parameter values θ t −1 and covariance matrix equal to the estimated covariance matrix of the posterior based on a Laplace approximation (Tierney 1986).

Hessian matrix of the log posterior distribution, which from Equation (13), is given by ∇ w ∇ w ln P w t, α = ∇ w ∑ n = 1 N ϕ x n t n - y n - A W = ∑ n = 1 N - e - w n ϕ n 1 + e - w n ϕ x n 2 ϕ x n ϕ x n T - A = - ∑ n = 1 N y n 1 - y n ϕ x n ϕ x n T - A = - Φ T B Φ + A (22).

WinBUGS code for implementing the model is given in Additional file 2. The presence of confounding was investigated by analysing the correlation matrix of the joint posterior distribution for all model parameters but especially the slope parameters.