Statistical methods generally have assumptions (eg, normality in linear regression models).
Violations of these assumptions can cause various issues, like statistical errors and biased …

Based on China's 30 provinces penal data, from 1990 to 2017, this paper uses the quantile
regression model to estimate the impact of fossil energy abundance and clean energy …

This study addresses antibiotic pollution in global water bodies by integrating machine
learning and optimization algorithms to develop a novel reverse synthesis strategy for …

Reliable estimates of when hominin taxa originated and went extinct are central to
addressing many paleoanthropological questions, including those relating to …

Culverts are stormwater structures that require ongoing condition assessment and proactive
maintenance for optimal performance to reduce flooding, especially in urban areas …

Bias correction is a common practice in climate sciences. However, bias-corrected climate
projections do not necessarily preserve signals in moments and quantiles compared to raw …

The notion of a zenpath and a zenplot is introduced to search and detect dependence in
high-dimensional data for model building and statistical inference. By using any measure of …

Deciding whether two measurement systems agree well enough to be used interchangeably
is important in medical and clinical contexts. Recently, the probability of agreement was …

The 24 h and 14-day relationship between indoor and outdoor PM2. 5, PM10, NO2, relative
humidity, and temperature were assessed for an elementary school (site 1), a laboratory …

We developed the Verbal Affective Memory Test-26 (VAMT-26), a computerized test to
assess verbal memory, as an improvement of the Verbal Affective Memory Test-24 (VAMT …