The joint distribution of residuals in the pedigree was modelled using a multivariate normal distribution with variance-covariance matrix proportional to the identity matrix.
The correlated SNPs are generated using a multivariate normal distribution function and the method developed in the R package HapSim (Montana, 2005).
These shifts are again generated using a multivariate normal distribution as estimated by the sample means and covariance as observed in PREMIER.
The MVH system segregates experimental peaks into three intensity classes and measures the point probability of matching a given combination of peaks by random chance using a multivariate hypergeometric distribution [17].
The most common approach has been to apply the method of independent contrasts [ 11], or alternatively, to model the data using a multivariate normal distribution which has a covariance structure derived from the phylogenetic tree.
These simulations generate random phenotypes as phylogenetic independent contrasts along the tree (for each node) using a multivariate normal distribution with zero means and a covariance matrix based on the observed phylogenetic independent contrasts.
The Bayesian kriging model assumes that spatial errors are modeled using a multivariate Gaussian distribution with covariance matrix expressed as a parametric function of the distance between pairs of points.
In total, 245 different pathway designs were obtained by the combination of the three experimental factors and expression submatrices were generated for each of them using a multivariate normal distribution.
The ranges of prediction (90% prediction intervals) were obtained using "parameter scan" in the SimBiology software, in which the parameter values were generated using a multivariate normal distribution with unit covariance matrix and a mean vector corresponding to the fitted parameter values.
Because λ and the two μ parameters have support on the real line, we can use a multivariate Normal distribution as proposal distribution.
