The partially linear multiplicative regression model is considered. This model, which becomes a partially linear regression model after taking logarithmic transformation, is useful in analyzing data with positive responses. Chen et al. (2010) mentioned that in many applications the size of relative error, rather than that of error itself, is the central concern of practitioners. We extend the c...

Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single input-output data set. Here we investigate the utility of various methods for estimating the probability distribution of this nominal parameter using only the data from this single experiment. The results are compared to the actual parameter distribution generated by many Mont...

We attempt at a logical characterization of reasoning about normality based on the intuition that a normal situation is represented by a stable set of default assumptions. Within the context of preferential consequence relations we shall define a normality operator B and study its logical properties. Finally we shall focus on the AGM-like postulates for the normality expansion, contraction and ...