Finding Optimal Normalizing Transformations via bestNormalize

TL;DR: In this paper , a deep learning model was used to predict the concentration of dissolved oxygen (DO), an important measure of water quality and river metabolism, using data from 580 US rivers.

Abstract: Solar energy is increasingly used to produce electricity in Europe, but the environmental impact of constructing and running solar parks (SP) is not yet well studied. Solar park construction requires partial vegetation removal and soil leveling. Additionally, solar panels may alter soil microclimate and functioning. In our study of three French Mediterranean solar parks, we analyzed:(1) effects of solar park construction on soil quality by comparing solar park soils with those of semi‐natural land cover types (pinewood and shrubland) and abandoned croplands (former vineyards); and (2) the effect of solar panels on soil microclimate, CO2 effluxes, and vegetation. We measured 21 soil properties of physical, chemical, and microbiological soil quality in one solar park and its surroundings to calculate integrated indicators of soil quality. We surveyed soil temperature and moisture, CO2 effluxes, and vegetation below and outside solar panels of three solar parks. Soil aggregate stability was reduced by SP construction resulting in a degradation of soil physical quality. Soil chemical quality and a general indicator of soil quality were lower in anthropogenic (SP and abandoned vineyards) than in semi‐natural (pinewood and shrubland) land cover types. However, differences between abandoned vineyards representing the preconstruction land cover type and solar parks were not significant. Solar panels reduced the soil temperature by 10% and soil CO2 effluxes by 50% but did not affect early successional plant communities. Long‐term monitoring is needed to evaluate the effects of solar panels on vegetation.

TL;DR: Using RNA sequencing (RNA-seq) in large, well-annotated cohorts of medulloblastoma, this paper showed that transcriptionally group 3 and group 4 entities exist as intermediates on a bipolar continuum.

TL;DR: Feature reduction significantly improves the performance of HCC prediction models by reducing the dimensionality of the data, leading to enhanced accuracy and reduced execution time.

TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.

TL;DR: The modern applied statistics with s is universally compatible with any devices to read, and is available in the digital library an online access to it is set as public so you can download it instantly.

TL;DR: In this article, a Laplace approximation is used to obtain an approximate restricted maximum likelihood (REML) or marginal likelihood (ML) for smoothing parameter selection in semiparametric regression.

TL;DR: This research presents a novel and scalable approach called “Smartfitting” that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of designing and implementing statistical models for regression models.