Covariant-contravariant simulation and conformance simulation generalize plain simulation and try to capture the fact that it is not always the case that “the larger the number of behaviors, the better”. We have previously studied some of their properties, showing that they can be presented as particular instances of the general notion of categorical simulation developed by Hughes and Jacobs an...

Processes characterized by high dimensional and mixture data challenge traditional statistical process control charts. In this study, we propose a multivariate control chart based on the Gower distance that can handle a mixture of continuous and categorical data. An extensive simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compa...

Abstract Modern approaches for the spatial simulation of categorical variables are largely based on multi-point statistical methods, where a training image is used to derive complex relationships using relevant patterns. In these approaches, simulated realizations driven by utilized, while statistics actual sample data ignored. This paper presents data-driven, high-order approach approximation ...

Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable statistical tool. We propose a Pearson chi-square based feature screening procedure for categorical response with ultrahigh dimensional categorical covariates. The proposed procedure can be directly ...

Abstract In this article we apply the maximum trimmed likelihood (MTL) approach (Hadi and Luceño 1997) to obtain the robust estimators of multivariate location and shape, especially for data mixed with continuous and categorical variables. The forward search algorithm (Atkinson 1994) is adapted to compute the proposed MTL estimates. A simulation study shows that the proposed estimator outperfor...

In high-dimensional settings, where the number of features p is much larger than the number of samples n, methods that systematically examine arbitrary combinations of features have only recently begun to be explored. However, none of the current methods is able to assess the association between feature combinations and a target variable while conditioning on a categorical covariate. As a resul...

It is well-known that the auditory perception of speech sounds is strongly influenced by the phonetic categories which divide up acoustic space. This paper approaches the problem of modeling categorical perception from the ground up, using a linear model of the tuning properties of auditory neurons – the spectro-temporal receptive field (STRF). An STRF which discriminates voiced from voiceless ...

In this paper, I propose a neurophysiologically plausible account for the evolution of arbitrary, categorical mental relationships. Topographic, or structure-preserving, mappings are widespread within animal brains. If they can be shown to generate behaviours in simulation, it is plausible that they are responsible for them in vivo. One behaviour has puzzled philosophers, psychologists and ling...