Logistic regression1 has been widely used in direct marketing applications to develop response and conversion models. Although attractively simple, logistic regression has been criticized for failing to capture the nonlinearity, and therefore possibly not leading to satisfactory results. Introduced by Hastie and Tibshirani, Generalized Additive Model2 (GAM) provides the ability to detect the no...

The generalized wordlength pattern (GWLP) introduced by Xu and Wu (2001) for an arbitrary fractional factorial design allows one to extend the use of the minimum aberration criterion to such designs. Ai and Zhang (2004) defined the J-characteristics of a design and showed that they uniquely determine the design. While both the GWLP and the J-characteristics require indexing the levels of each f...

We estimate and compare two models, the Generalized Taylor Economy (GTE) and the Multiple Calvo model (MC), that have been built to model the distributions of contract lengths observed in the data. We compare the performances of these models to those of the standard models such as the Calvo and its popular variant, using the ad hoc device of indexation. The estimations are made with Bayesian te...

In this paper, we study the advanced differential equations r(t) x (t) α–1 x (t) + n i=1 p i (t) x(t + τ i (t)) α–1 x(t + τ i (t)) = 0 and r(t)(y(t) – P(t)y(t – τ)) + n i=1 p i (t)f (y(t + σ)) = 0. By using the generalized Riccati transformation and the Schauder-Tyichonoff theorem, we establish the conditions for the existence of positive solutions of the above equations.

We present a novel ensemble of logistic linear regressors that combines the robustness of online Bayesian learning with the flexibility of ensembles. The ensemble of classifiers are built on top of a Randomly Varying Coefficient model designed for online regression with the fusion of classifiers done at the level of regression before converting it into a class label using a logistic link functi...

Protecting sensitive micro data prior to publishing or passing the data itself on is a crucial aspect: A trade-off between sufficient disclosure control and analyzability needs to be found. This paper presents a starting point to evaluate the effect of k-anonymity microaggregated data in (generalized) linear regression. Taking a rigorous imprecision perspective, microaggregated data are underst...