A Bayesian analysis for factorial experiments is presented, using finite mixture distributions to model the main effects and interactions. This allows both estimation and an analogue of hypothesis testing in a posterior analysis using a single prior specification. A detailed formulation based on this approach is provided for the case of the two-way model with replication, allowing interactions....

We are interested in the intensive use of Factorial Correspondence Analysis (FCA) for large-scale content-based image retrieval. Factorial Correspondence Analysis, is a useful method for analyzing textual data, and we adapt it to images using the SIFT local descriptors. FCA is used to reduce dimensions and to limit the number of images to be considered during the search. Graphics Processing Uni...

Social scientists use conjoint analysis, which is based on randomized experiments with a factorial design, to analyze multidimensional preferences in a population. In such experiments, several factors, each with multiple levels, are randomized to form a large number of possible treatment conditions. To explore causal interaction in factorial experiments, we propose a new definition of causal in...

This paper presents a mixed-level factorial design for scalability analysis of the Zereal Massively Multiplayer Game Simulator. The selected factors are number of killers, monsters and CPUs in addition to the killer and monster vision radius. The analysis show that the factors explain approximately 85% of the model (measured in square of errors), which is surprisingly good since the simulation ...

OBJECTIVE The objective of this investigation was to evaluate the relative contribution of variables in the crown-cement-tooth system that can influence magnitude of maximum principal stress in all-ceramic crowns. METHODS.: Factorial analysis was performed to calculate the coefficients of main and interactive effects of seven variables on maximum stress distribution in a series of finite elemen...

We presented an alternative way to verify the relative contribution to the total variance, of the sources of variation due to populations (P), individuals within populations (I), the (P*I) interaction, and the standard error of the following parameter estimates: total (F) and intrapopulation (f) fixation indices, and divergence among populations ( ). The knowledge of this relative contribution ...