Sentence examples for models for multivariate from inspiring English sources

Zhang, Y., Zhou, H., Zhou, J. & Sun, W. Regression models for multivariate count data.

Our paper proposes a methodology to construct approximate models for multivariate stochastic dynamic simulations using kriging, by combining ideas from design of experiments and dynamic systems modeling.

Our paper presents a methodology to construct approximate models for multivariate stochastic dynamic simulations using GPM, by combining ideas from design of experiments, spatial statistics and dynamic systems modeling.

The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses).

There is a need for tractable models for multivariate data with nonstandard dependence structures.

We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data.

The contribution is to introduce a novel model for multivariate data where some response variables are discrete and some are continuous.

In doing so, we make clear some special features of the GoM model for multivariate analysis of high dimensional, discrete data.

We then present a method and describe the proposed formulation for the of cost model for multivariate situations in "Proposed cost model".

We used χ 2 or t test for univariate analysis and Cox proportional hazards model for multivariate analysis to identify factors associated with mortality.

Partial correlation was used to build up the model for multivariate analysis.