New technologies are permitting larger scale and more quantitative studies of signalling networks. The large data sets that are obtained from these studies can be analysed by data-driven modelling ...

Missing data is a major issue in many applied problems, especially in the biomedical sciences. We review four common approaches for inference in generalized linear models (GLMs) with missing covariate ...

Econometric models estimating parameters for agricultural policy analysis increasingly rely on unbalanced panels of farm-level data. Since such models have often been estimated through simplified ...

Discover how data mining uncovers patterns in big data to boost marketing, sales, fraud detection, and more using advanced techniques.

This white paper by industry expert Alec Sharp illustrates these points and provides specific guidelines and techniques for a business-oriented approach to data modeling. Examples demonstrate how ...

These techniques are used to curate, inspect and analyse data to draw insights; machine learning, which creates algorithms that learn automatically from data; and artificial intelligence, where ...