Sentence examples for multivariate normal models from inspiring English sources

These good frequentist properties results agree with previous literature on Bayesian reference analyses for other models such as, for example, Gaussian random fields (Berger et al. 2001), Markov random fields (Ferreira and De Oliveira 2007), multivariate normal models (Sun and Berger 2007), and elapsed times in continuous-time Markov chains (Ferreira and Suchard 2008).

Two distinct approaches are used the multivariate normal model and the chained equations approach.

The multivariate normal model was introduced by Rubin (1987; see also Little & Rubin 2002).

To begin with, the multivariate normal model has theoretical underpinnings whereas MICE does not.

In this paper, we reviewed two approaches to multiple imputation the multivariate normal model and the chained equations approach.

Peugh and Enders (2004) demonstrated the use of multiple imputation using the multivariate normal model in the context of the Longitudinal Study of American Youth.

A multivariate normal model was assumed for.

This multivariate normal model fitted the data adequately.

This means the normal copula model is more robust than the multivariate normal model.

The simulated data (for the current study) were generated using a multivariate normal model.

Two separate analyses were performed based on the multivariate normal model with adjustment for local dependence and item bias.