Advancements in Bayesian spatial and spatio-temporal modelling have been observed in
recent years. Despite this, there are unresolved issues about the choice of appropriate …

Specification of the prior distribution for a Bayesian model is a central part of the Bayesian
workflow for data analysis, but it is often difficult even for statistical experts. In principle, prior …

We discuss hypothesis testing and compare different theories in light of observed or
experimental data as fundamental endeavors in the sciences. Issues associated with the p …

In football research,'small'trials with low statistical power are common. On the elite level, the
inherently low number of participants obviously conflicts with the relevance of even tiny …

Probabilistic (Bayesian) modeling has experienced a surge of applications in almost all
quantitative sciences and industrial areas. This development is driven by a combination of …

Abstract Satellite-based Normalized Difference Vegetation Index (NDVI) time series data are
conducive for near-real-time (NRT) monitoring of crop progress, but they commonly suffer …

In a century where toxicology and chemical risk assessment are embracing alternative
methods to animal testing, there is an opportunity to understand the causal factors of …

Abstract Previous research (Mirault, Snell, & Grainger, 2018) has demonstrated that subjects
sometimes incorrectly judge an ungrammatical sentence as grammatical when it is created …

Apraxia of speech is a motor speech disorder that occurs after lesions to the left cerebral
hemisphere, most often concomitant with aphasia. It requires specific approaches in the …

Some situations require cognitive flexibility, whereas others call for cognitive stability.
Recent theories posit lower-level associative learning processes as the basis of contextual …