Discrete choice models have played an important role in transportation modeling for the last 25 years. They are namely used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justiications. Moreover, several packages and tools are available to help practionners using these models for real applications, making discrete choice models ...

background and objectives: lactobacillus delbrueckii ssp bulgaricus is widely used in dairy industries as a starter for yogurt production. this study was designed using response surface methodology (rsm) in 12 batch ph-controlled cultures of lactobacillus delbrueckii sub-ssp. bulgaricus for determining the effect of temperature and ph on the biomass production of a native strain of l. bulgaricu...

We consider the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted with a nonparametric function of a continuous covariate. This model is tailormade to address known d...

This paper aims to install Latent trait on Association Rule Mining for the semantic analysis of consumer behavior patterns. We adapt Item Response Theory, a famous educational testing model, in order to derive interesting insights from rules by Latent trait. The primary contributions of this paper are fourfold. (1) Latent trait as an unified measure can measure interestingness of derived rules ...

In many machine learning applications that deal with sequences, there is a need for learning algorithms that can effectively utilize the hierarchical grouping of words. We introduce Word Taxonomy guided Naive Bayes Learner for the Multinomial Event Model (WTNBL-MN) that exploits word taxonomy to generate compact classifiers, and Word Taxonomy Learner (WTL) for automated construction of word tax...

In this tutorial we show how complete hierarchical multinomial marginal (HMM) models for categorical variables can be defined, estimated and tested using the hmmm package.