The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...

R is a powerful open source programming environment primarily known for its statistical capabilities. In this course we will cover some advanced applications of R: distributed computing using the ...

We review basic modeling approaches for failure and maintenance data from repairable systems. In particular we consider imperfect repair models, defined in terms of virtual age processes, and the ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, new statistical analysis methods are being developed to make more out of ...

'Genomic prediction' has been used by researchers to predict the performance of hybrid rice. Genomic prediction is a new technology that could potentially revolutionize hybrid breeding in agriculture.

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, ...