4 papers
Likelihood-based inference for modelling packet transit from thinned flow summaries
Prosha A. Rahman, Boris Beranger, Matthew Roughan +1
The substantial growth of network traffic speed and volume presents practical challenges to network data analysis. Packet thinning and flow aggregation protocols such as NetFlow re…
Logistic regression models for aggregated data
Tom Whitaker, Boris Beranger, Scott A. Sisson
Logistic regression models are a popular and effective method to predict the probability of categorical response data. However inference for these models can become computationally…
Composite likelihood methods for histogram-valued random variables
Thomas Whitaker, Boris Beranger, Scott A. Sisson
Symbolic data analysis has been proposed as a technique for summarising large and complex datasets into a much smaller and tractable number of distributions -- such as random recta…
High-dimensional inference using the extremal skew- process
B. Beranger, A. G. Stephenson, S. A. Sisson
Max-stable processes are a popular tool for the study of environmental extremes, and the extremal skew- process is a general model that allows for a flexible extremal dependence…