1,665 Results Found

Stochastic simulation has a prominent position in a variety of scientific domains including those of environmental and water resources sciences. This is due to the numerous applications that can benefit from it, such as risk-related studies. In such...

Meta-analysis techniques allow researchers to jointly analyse different studies to determine common effects. In the field of transcriptomics, these methods have gained popularity in recent years due to the increasing number of datasets that are avail...

Terrestrial Laser Scanning (TLS) enables rapid, automatic, and detailed 3D representation of surfaces with an easily handled scanner device. TLS, therefore, shows great potential for use in Forest Inventories (FIs). However, the lack of well-establis...

NMR spectroscopy is a widely used method for the detection and quantification of metabolites in complex biological fluids. However, the large number of metabolites present in a biological sample such as urine or plasma leads to considerable signal ov...

The complex Pearson (CP) distributions are a family of probability models for count data generated by the Gaussian hypergeometric function with complex arguments. The complex triparametric Pearson (CTP) distribution and its biparametric versions, the...

This paper describes and evaluates the educational interest of LearningRlab, an educational R package developed for teaching statistics in computer science engineering. The package was developed by final degree project students to be used as an educa...

Identifying the mutational processes that shape the nucleotide composition of the mitochondrial genome (mtDNA) is fundamental to better understand how these genomes evolve. Several methods have been proposed to analyze DNA sequence nucleotide composi...

The 21st century has witnessed a growing interest in the analysis of time series data. While most of the literature on the topic deals with real-valued time series, ordinal time series have typically received much less attention. However, the develop...

Ambient fine particulate matter of size less than 2.5 μm in aerodynamic diameter (PM2.5) is a key ambient air pollutant that has been linked to numerous adverse health outcomes. Reliable estimates of PM2.5 are important for supporting epidemiologi...

Metabolomes comprise constitutive and non-constitutive metabolites produced due to physiological, genetic or environmental effects. However, finding constitutive metabolites and non-constitutive metabolites in large datasets is technically challengin...

Ridge regression is one of the most popular shrinkage estimation methods for linear models. Ridge regression effectively estimates regression coefficients in the presence of high-dimensional regressors. Recently, a generalized ridge estimator was sug...

Background: Colorectal cancer is a multifactorial malignancy implicating a wide variety of risk factors, such as genetic, environmental, nutritional, and lifestyle factors, leading to a certain heterogeneity in the development of the disease. Colorec...

Water resources systems, as facilities for storing water and supplying demands, have been critically important due to their operational requirements. This paper presents the applications of an R package in a large-scale water resources operation. The...

Explanatory item response modeling (EIRM) enables researchers and practitioners to incorporate item and person properties into item response theory (IRT) models. Unlike traditional IRT models, explanatory IRT models can explain common variability ste...

Patent Box regimes are a tax relief incentive promoted by governments to encourage the R&D activities of enterprises. The literature developed on Patent Box is still examining the effects on certain economic variables. Thus, this research conduct...

Background/Objectives: We present hidecan, an R package for generating visualisations that summarise the results of one or more genome-wide association studies (GWAS) and differential expression analyses, as well as manually curated candidate genes,...

Global biodiversity change creates a need for standardized monitoring methods. Modelling and mapping spatial patterns of community composition using high-dimensional remotely sensed data requires adapted methods adequate to such datasets. Sparse gene...

Forest population structure and dynamics represent core research areas in forest ecology, encompassing multiple components such as quantitative analyses of population changes, age structure, life tables, and species dynamics within specific spatial a...

Although bulked segregant analysis (BSA) has been used extensively in genetic mapping, user-friendly tools which can integrate current algorithms for researchers with no background in bioinformatics are scarce. To address this issue, we developed an...

Integrated environmental modelling requires coupling sub-models at different spatial and temporal scales, thus accounting for change of support procedures (aggregation and disaggregation). We introduce the R-package spatio-temporal Uncertainty Propag...

The number of global open-source hydrometeorological datasets and models is large and growing. However, with a constantly growing demand for services and tools from stakeholders, not only in the water sector, we still lack simple solutions, which are...

Forests are threatened globally by deforestation. Forest restoration at the landscape scale can reduce these threats. Ground-based and remote sensing inventories are needed to assess restoration success. Fractional canopy cover estimated from forest...

Fire spread behavior models are used to estimate fire behavior metrics, fire hazard, exposure, and risk across the landscape. One of the most widely used fire spread models is the minimum travel time (MTT), which requires a very time-consuming, inter...

This paper introduces an R package ForecastTB that can be used to compare the accuracy of different forecasting methods as related to the characteristics of a time series dataset. The ForecastTB is a plug-and-play structured module, and several forec...

Deep sequencing has revealed that the 16S rRNA gene composition of the human microbiome can vary between populations. However, when existing data are insufficient to address the desired study questions due to limited sample sizes, Dirichlet mixture m...

Background: The opioid crisis remains a significant public health challenge in North America, highlighted by the substantial need for tools to analyze and understand opioid potency and prescription patterns. Methods: The OralOpioids package automates...

Several ecological data types, especially microbiome count data, are commonly sample-wise normalized before analysis to correct for sampling bias and other technical artifacts. Recently, we developed an algorithm for the normalization of ecological c...

Spatiotemporal models for count data are required in a wide range of scientific fields, and they have become particularly crucial today because of their ability to analyze COVID-19-related data. The main objective of this paper is to present a review...

R is one of the most powerful programming languages for conducting data analysis, modeling, and visualization. Although it is widely utilized in biodiversity conservation research, the comprehensive trends in R and R package usage and patterns in the...

Monitoring vegetation disturbances using long remote sensing time series is crucial to support environmental management, biodiversity conservation, and adaptation strategies to climate change from global to local scales. However, it is difficult to a...

In this article, a two-tiered 2D tool is described, called ⟨φ,δ⟩ diagrams, and this tool has been devised to support the assessment of classifiers in terms of accuracy and bias. In their standard versions, these diagrams provide information, as the u...

Sparse estimation through regularization is gaining popularity in psychological research. Such techniques penalize the complexity of the model and could perform variable/path selection in an automatic way, and thus are particularly useful in models t...

The paper describes rich, a new R package to perform species richness estimation and comparison. Species richness is the simplest surrogate for the more complex concept of species biodiversity. It is relatively easy to assess although estimations str...

Wildland fire and ecological researchers use empirical and semi-empirical modeling systems to assess fire behavior and danger. This technical note describes the firebehavioR package, a porting of two fire behavior modeling systems, Crown Fire Initiat...

We provide a general overview of Bayesian model averaging (BMA) along with the concept of jointness. We then describe the relative merits and attractiveness of the newest BMA software package, BMS, available in the statistical language R to implement...

This article introduces the R package pspatreg, which is publicly available for download from the Comprehensive R Archive Network, for estimating semiparametric spatial econometric penalized spline (P-Spline) models. These models can incorporate a no...

Prefabricated construction (PC) offers advantages to the architecture, engineering, and construction (AEC) industry such as quality production, fast project completion, low waste output, high environmental sensitivity, and high security. Although PC...

Cognitive diagnosis models (CDMs) are confirmatory latent class models that provide fine-grained information about skills and cognitive processes. These models have gained attention in the last few years because of their usefulness in educational and...

RNA sequencing (RNA-seq) has become a standard method for profiling gene expression, yet genomic DNA (gDNA) contamination carried over to the sequencing library poses a significant challenge to data integrity. Detecting and correcting this contaminat...

In this article, we explain and demonstrate how to model norm scores with the cNORM package in R. This package is designed specifically to determine norm scores when the latent ability to be measured covaries with age or other explanatory variables s...

The filtered monotonic polynomial (FMP) model is a semi-parametric item response model that allows flexible response function shapes but also includes traditional item response models as special cases. The flexmet package for R facilitates the routin...

The recent incursions of African swine fever (ASF), a severe, highly contagious, transboundary viral disease that affects members of the Suidae family, in Europe and China have had a catastrophic impact on trade and pig production, with serious impli...

Meta-analysis is an indispensable tool for synthesizing statistical results obtained from individual studies. Recently, non-Bayesian estimators for individual means were proposed by applying three methods: the James–Stein (JS) shrinkage estimat...

In this study, we present a package for R that is intended as a professional tool for the management and analysis of data from educational tests and useful both in high-stakes assessment programs and survey research. Focused on psychometric models ba...

Combining items from an item pool into test forms (test assembly) is a frequent task in psychological and educational testing. Although efficient methods for automated test assembly exist, these are often unknown or unavailable to practitioners. In t...

The described R package allows to estimate Dynamic Model Averaging (DMA), Dynamic Model Selection (DMS) and Median Probability Model. The original methods, and additionally, some selected modifications of these methods are implemented. For example th...

Much of modern science takes place in a computational environment, and, increasingly, that environment is programmed using R, Python, or Julia. Furthermore, most scientific data now live on the cloud, so the first step in many workflows is to query a...

Background: PhenoMetaboDiff is a novel R package for computational analysis and visualization of data generated by Biolog Phenotype Mammalian Microarrays (PM-Ms). These arrays measure the energy production of mammalian cells in different metabolic en...

Background: The evolution of “omic” technologies, which measure all biological molecules of a specific type (e.g., genomics), has enabled rapid and cost-effective data acquisition, depending on the technique and sample size. This, however...

Small-compound databases contain a large amount of information for metabolites and metabolic pathways. However, the plethora of such databases and the redundancy of their information lead to major issues with analysis and standardization. A lack of p...