The present research examines the differential impact of the importance of internally and externally sourced information and knowledge and its relationship to absorptive capacity and firm performance. In addition, this analysis deals directly with the unobservable heterogeneity amongst firms that is generally viewed as the raison d'être for a unique resource based perspective of organizational ...

Mixture models have been widely used in modeling of continuous observations. For the possibility to estimate the parameters of a mixture model consistently on the basis of observations from the mixture, identifiability is a necessary condition. In this study, we give some results on the identifiability of multivariate logistic mixture models.

This work proposes two approaches to improve the poolbased active learning strategy ’Multi-Class Probabilistic Active Learning ’ (McPAL) by using two kernel functions based on Gaussian mixture models (GMMs). One uses the kernels for the instance selection of the McPAL strategy, the second employs them in the classification step. The results of the evaluation show that using a different classifi...

Precipitation forecast verification is essential to the quality of a forecast. The Gaussian Mixture Model can be used to approximate the precipitation of several rain bands and provide a concise view of the data, which is especially useful for comparing forecast and observation data. The robustness of such comparison mainly depends on the consistency of and the correspondence between the extrac...

Modelling covariance structure in the analysis of repeated measures data, Statist. Med. A new class of multivariate skew distributions with applications to Bayesian regression models, The Canadion Journal of Analysis for the Student-t regression model.