Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial
interpolation problem to space and time dimensions. Here, we review the statistical, physical …

Measurement error and misclassification of variables frequently occur in epidemiology and
involve variables important to public health. Their presence can impact strongly on results of …

Abstract We describe sleuth (http://pachterlab. github. io/sleuth), a method for the differential
analysis of gene expression data that utilizes bootstrapping in conjunction with response …

A valuable overview of the most important ideas and results in statistical modeling Written by
a highly-experienced author, Foundations of Linear and Generalized Linear Models is a …

Current sequencing methods produce large amounts of data, but genome assemblies
constructed from these data are often fragmented and incomplete. Incomplete and error …

Measurement error is ubiquitous in experimental work. It leads to imperfect statistical
controls, attenuated estimated effects of elicited behaviors, and biased correlations between …

Many evolutionary biologists are concerned with the tremendous amount of diversity of
species, and their phenotypes, that we can currently observe in nature, and one of the most …

By modeling variables over time it is possible to investigate the Granger-causal cross-
lagged associations between variables. By comparing the standardized cross-lagged …

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

INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting
a broad class of Bayesian regression models. No samples of the posterior marginal …