Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

In linear regression problems with many predictors, penalized regression techniques are
often used to guard against overfitting and to select variables relevant for predicting an …

We have collected transit times for the TRAPPIST-1 system with the Spitzer Space
Telescope over four years. We add to these ground-based, HST, and K2 transit-time …

Imbalanced anthropogenic inputs of nitrogen (N) and phosphorus (P) have significantly
increased the ratio between N and P globally, degrading ecosystem productivity and …

State–space models (SSMs) are an important modeling framework for analyzing ecological
time series. These hierarchical models are commonly used to model population dynamics …

Animal foraging and competition are defined by the partitioning of three primary niche axes:
space, time, and resources. Human disturbance is rapidly altering the spatial and temporal …

The ideal stock assessment would be able to estimate all of the key parameters related to
population processes within a framework that assigns appropriate weight to the data, fits the …

The foundational ecosystem processes of gross primary production (GPP) and ecosystem
respiration (ER) cannot be measured directly but can be modeled in aquatic ecosystems …

Consider a coherent system, in which the degradation processes of its performance
characteristics are positively correlated, this paper systematically investigates a bivariate …

Animals and plants are shifting the timing of key life events in response to climate change,
yet despite recent documentation of escalating phenological change, scientists lack a full …