A two-dimensional method based on basic and mixed models for simulation of liquid phase sintering of a porous structure will be developed. These models will be tested in order to conduct a study of diffusion phenomena and gravitational effects on microstructural evolution during liquid phase sintering of a W-Ni system.

This paper examines the relationship between causal ordering and two temporal abstraction techniques, namely generation of mixed models from dynamic models and aggregation of nearly decomposable models. The paper defines two notions of causal equivalence between an original model and its abstraction or its elaboration. Then, it shows that when the constraint for a uniform temporal grain size fo...

Bivariate linear mixed models are useful when analyzing longitudinal data of two associated markers. In this paper, we present a bivariate linear mixed model including random effects or first-order auto-regressive process and independent measurement error for both markers. Codes and tricks to fit these models using SAS Proc MIXED are provided. Limitations of this program are discussed and an ex...

In this paper we undertake an acoustic analysis of dental and alveolar segments in Mapudungun, an indigenous language of Chile. We calculate locus equations for dental and alveolar segment pairs of different manners. We find that dentals differ from alveolars of the corresponding manner in lowering the onset F2 of following vowels. We validate these results by means of a linear mixed model anal...

This paper deals with different chain graph interpretations and the relations between them in terms of representable independence models. Specifically, we study the Lauritzen-Wermuth-Frydenberg, Andersson-Madigan-Pearlman and multivariate regression interpretations and present the necessary and sufficient conditions for when a chain graph of one interpretation can be perfectly translated into a...

Topic variance has a greater effect on performances than system variance but it cannot be controlled by system developers who can only try to cope with it. On the other hand, system variance is important on its own, since it is what system developers may affect directly by changing system components and it determines the differences among systems. In this paper, we face the problem of studying ...

Statistical models that include random effects are commonly used to analyze longitudinal and correlated data, often with strong and parametric assumptions about the random effects distribution. There is marked disagreement in the literature as to whether such parametric assumptions are important or innocuous. In the context of generalized linear mixed models used to analyze clustered or longitu...