Previous surveys of the literature have shown that reports of statistical analyses often lack
important information, causing lack of transparency and failure of reproducibility. Editors and …

Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

For the vast majority of stars in the second Gaia data release, reliable distances cannot be
obtained by inverting the parallax. A correct inference procedure must instead be used to …

Novelty detection is the task of classifying test data that differ in some respect from the data
that are available during training. This may be seen as “one-class classification”, in which a …

Publisher Description (unedited publisher data) An essential textbook for any student or
researcher in biology needing to design experiments, sampling programs or analyse the …

Kernel smoothing has greatly evolved since its inception to become an essential
methodology in the data science tool kit for the 21st century. Its widespread adoption is due …

This article considers the application of two families of nonlinear autoregressive models, the
logistic (LSTAR) and exponential (ESTAR) autoregressive models. This includes the …

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Account Menu Find a journal Publish with us Track your research Search Cart Book cover Linear …

This article considers how to estimate Bayesian credible and highest probability density
(HPD) intervals for parameters of interest and provides a simple Monte Carlo approach to …

Amongmanyexcitingdevelopmentsinstatistic…, nonlineartimeseriesanddata-
analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In …