Functional data analysis can be challenging when the functional objects are sampled only very sparsely and unevenly. Most approaches rely on smoothing to recover the underlying functional object from the data which can be difficult if the data is irregularly distributed. In this paper we present...

This research uses functional data modelling to study the price formation process of online auctions. It conceptualizes the price curve and its first and second derivatives(velocity and acceleration respectively) as the primary objects of interest. Together these three functional objects permit...

Political campaigning has become a multi-million dollar business. A substantial proportion of a campaign's budget is spent on voter targeting, i.e. to identify and influence as many voters as possible to vote. Based on data, campaigns use statistical tools to provide a basis for decision on whom...

Censored count data are encountered in many applications, often due to a data collection mechanism that introduces censoring. A common example is questionnaires with question answers of the type 0,1,2,3. We consider the problem of predicting a censored output variable Y, given a set of complete...

Poisson regression is a popular tool for modeling count data and is applied in a vast array of applications from the social to the physical sciences and beyond. Real data, however, are often over- or under-dispersed and, thus, not conducive to Poisson regression. We propose a regression model...