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This paper introduces a new multivariate approach for jointly modeling crash counts by severity data based on Multivariate Poisson-Lognormal models. Although the crash frequency by severity data are multivariate in nature, they have often been analyzed by modeling each severity level separately without taking into account correlations that exist among different severity levels. The new Multivar...

This paper analyses results from an investigation into the determinants of biotechnology innovation in New Zealand using a comprehensive new dataset. The theoretical framework is based on a synthesis of hypotheses drawn from four strands of the innovation literature and the empirical work utilises Poisson regression methods. The data provides strong support for the idea that smaller enterprises...

background: in the case of sensitive questions such as number of alcoholics known, majority of respondents might give an answer of zero. poisson regression model (p) is the standard tool to analyze count data. however, p provides poor fit in the case of zero inflated counts, when over-dispersion exists. therefore, the questions to be addressed are to compare performance of alternative count reg...

We answer positively a question of Kaimanovich and Vershik from 1979, showing that the final configuration of lamps for simple random walk on the lamplighter group over Z (d ≥ 3) is the Poisson boundary. For d ≥ 5, this had been shown earlier by Erschler (2011). We extend this to walks of more general types on more general groups.

We present a novel phoneme-based student model for spelling training. Our model is data driven, adapts to the user and provides information for, e.g., optimal word selection. We describe spelling errors using a set of features accounting for phonemic, capitalization, typo, and other error categories. We compute the influence of individual features on the error expectation values based on previo...