OBJECTIVE Statistical models, such as linear or logistic regression or survival analysis, are frequently used as a means to answer scientific questions in psychosomatic research. Many who use these techniques, however, apparently fail to appreciate fully the problem of overfitting, ie, capitalizing on the idiosyncrasies of the sample at hand. Overfitted models will fail to replicate in future s...

Identifying the number of classes in Bayesian finite mixture models is a challenging problem. Several criteria have been proposed, such as adaptations of the deviance information criterion, marginal likelihoods, Bayes factors, and reversible jump MCMC techniques. It was recently shown that in overfitted mixture models, the overfitted latent classes will asymptotically become empty under specifi...

This paper suggests a new procedure for evaluating the fit of a dynamic structural economic model. The procedure begins by augmenting the variables in the model with just enough stochastic error so that the model can exactly match the second moments of the actual data. Measures of fit for the model can then be constructed on the basis of the size of this error. The procedure is applied to a sta...

A new class of statistical models is proposed for the analysis of longitudinal data, especially those from growth studies. The models are all derived from a simple univariate two-level polynomial model. It is shown that they make efficient use of available data, and can handle a very wide range of problems. They have several important advantages over existing procedures.

We argue, that generative probabilistic models should be used to detect user activities, and we discuss two approaches to create those model from symbolic descriptions.

While recent recordings from neural populations show beyond-pairwise, or higher-order, correlations (HOC), we have little understanding of how HOC arise from network interactions and of how they impact encoded information. Here, we show that input nonlinearities imply HOC in spin-glass-type statistical models. We then discuss one such model with parametrized pairwise- and higher-order interacti...

Ecological risk assessment at the population level often involves predicting the effects of a particular change in the land-use patterns on the viability of native species. A common method of addressing such questions is modeling the metapopulation dynamics of the species in the landscape. However, the landscape and, as a result, the spatial structure of the metapopulation usually do not remain...

We analyze the variability in the x-ray lightcurves of the black hole candidate Cygnus X-1 by linear and nonlinear time series analysis methods. While a linear model describes the overall second order properties of the observed data well, surrogate data analysis reveals a significant deviation from linearity. We discuss the relation between shot noise models usually applied to analyze these dat...