Abstract The use of network analysis to investigate social structures has recently seen a rise due the high availability data and numerous insights it can provide into different fields. Most analyses focus on topological characteristics networks estimation relationships between nodes. We adopt perspective by considering whole as random variable conveying effect an exposure response. This point ...

This paper considers computational aspects of the problem of elimination of variables. More precisely, the problem of elimination of latent variables in models is addressed in the behavioral framework. In earlier contributions on this theme, the model classes of infinitely smooth C and square integrable L2 linear time-invariant systems have been considered. For both system classes, conditions f...

The naive Bayes model makes the often unrealistic assumption that the feature variables are mutually independent given the class variable. We interpret a violation of this assumption as an indication of the presence of latent variables, and we show how latent variables can be detected. Latent variable discovery is interesting, especially for medical applications, because it can lead to a better...

PLS Path Modeling is a widely used approach in marketing. In that field, relationships between latent variables are frequently nonlinear. This nonlinearity is usually defined by a piecewise linear function. In this talk, we present an approach to include non linear transformations of the latent variables in the PLS path modeling algorithm with monotonic B-splines. We use optimal scaling methods...