The wide and growing popularity of online auctions creates enormous amounts of publicly available bid data providing an important topic for research. These data pose unique statistical challenges because of their special structures. This research focuses on methods for representing, visualizing,...

Semi-continuous data arise in many applications where naturally-continuous data become contaminated by the data generating mechanism. The resulting data contain several values that are too frequent, and in that sense are a hybrid between discrete and continuous data. The main problem is that...

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...

We introduce a semiparametric approach for modelling the effect of concurrent events on an outcome of interest. Concurrency manifests itself as temporal and spatial dependences. By temporal dependence we mean the effect of an event in the past. Modelling this effect is challenging since events...

This paper presents a novel intelligent bidding system, called SOABER (Simultaneous Online Auction BiddER), which monitors simultaneous online auctions of high-value fine art items. It supports decision-making by maximizing bidders' surpluses and their chances of winning an auction. One key...

Forecasting prices in online auctions is important for both buyers and sellers. With good forecasts, bidders can make informed bidding decisions and sellers can select the right time and place to list their products. While information from other auctions can help forecast an ongoing auction, it...