There are two main research traditions for analyzing market basket data that exist more or less independently from each other, namely exploratory and explanatory model types. Exploratory approaches are restricted to the task of discovering cross-category interrelationships and provide marketing...

Discovering the preferences and the behaviour of consumers is a key challenge in marketing. Information about such topics can be gathered through surveys in which the respondents must assign a score to a number of items. In this article we suggest a strategy to analyze such data and achieve this...

After years of stagnancy, PLS path modeling has recently attracted renewed interest from applied researchers in marketing. At the same time, the availability of software alternatives to Lohmöller's LVPLS package has considerably increased (PLS-Graph, PLS-GUI, SPAD-PLS, SmartPLS). To help the...

Exploratory factor analysis (EFA) is an important tool in data analyses, particularly in social science. Usually four steps are carried out which contain an large number of options. One important option is the number of factors and the association of variables with a factor. Our tools aim to...

Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, to date applications of ICLV models in marketing are still rare. The...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...

Computational Statistics is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. In this article, we will discuss the motivation, history, some specialties, and the future scope of this journal.

Linear Methods are often used to compute approximate solutions to dynamic models, as these models often cannot be solved analytically. Linear methods are very popular, as they can easily be implemented. Also, they provide a useful starting point for understanding more elaborate numerical...