Sentence examples for multivariate normal and from inspiring English sources

Residuals e are normally distributed e| ~ MVN 0, R), where MVN stands for multivariate normal, and R = I.

Additionally we describe multivariate normal and multinomial cases.

We give illustrative examples based on the multivariate normal and multivariate Student t distributions.

Limiting efficiencies of the tests and treatment effect estimates are found in the multivariate normal and t distribution cases.

To do that, first, they employed two transformations to decrease the inherent skewness involved in multi-attribute processes and made the distribution of quality characteristics almost multivariate normal and diminished correlations between the attributes.

A one sample statistic is derived for the analysis of repeated measures design when the data are multivariate normal and the dimension, d, can be large compared to the sample size, n, i.e. d>n.

Christensen and Lund [ 14] did not rely on equation (7) to derive H, but they computed the mean of the missing genotypes conditional on the observed genotypes as: However, this is valid only for multivariate normal variables, and multivariate normality is not a good approximation for the distribution of marker covariates.

In this situation, where the covariance structure of g1 and g2 is determined entirely by the pedigree, it is easy to see that ε in equation (7) is uncorrelated to g2, and therefore if g1 and g2 are multivariate normal, ε and g2 are independent.

We give examples of chained equations algorithms that satisfy the non-informative margins condition when the joint model is the multivariate normal model and the saturated multinomial model, and examples where this condition is not satisfied when the joint model is an unsaturated multinomial model and the general location model.

Indeed, we additionally performed similar simulation studies to those shown for the UK700 data but under a simulated multivariate Normal scenario and observed perfect agreement between approaches (1) and (2) except when we allowed the missingness in the predictor to depend on the outcome and when we violated the multivariate normal assumption by log-transforming one of the predictors.

Recently, several reported methods aim to compute gene-wise P values, such as GATES [ 12], which adapts the Simes' test within each gene, VEGAS [ 13], which builds on the multivariate normal distribution and takes into account pairwise LD values, and the SNP-set analysis [ 14].