Digital Commons Network^™

Passed: Calculate Power And Sample Size For Two Sample Tests, Jinpu Li, Ryan .. Knigge, Kaiyi Chen, Emily V. Leary

The R Journal

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.

Automatic Time Series Forecasting With Ata Method In R: Ataforecasting Package, Ali Sabri Taylan, Güçkan Yapar, Hanife Taylan Selamlar

The R Journal

Ata method is a new univariate time series forecasting method that provides innovative solutions to issues faced during the initialization and optimization stages of existing methods. The Ata method’s forecasting performance is superior to existing methods in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or deseasonalized time series, where the deseasonalization can be performed via any preferred decomposition method. The R package ATAforecasting was developed as a comprehensive toolkit for automatic time series forecasting. It focuses on modeling all types of time series components with any preferred Ata methods and handling seasonality patterns by …

Robustbf: An R Package For Robust Solution To The Behrens-Fisher Problem, Gamze Güven, ŞÜkrü Acıtaş, Hatice ŞAmkar, Birdal ŞEnoğLu

The R Journal

Welch’s two-sample t-test based on least squares (LS) estimators is generally used to test the equality of two normal means when the variances are not equal. However, this test loses its power when the underlying distribution is not normal. In this paper, two different tests are proposed to test the equality of two long-tailed symmetric (LTS) means under heterogeneous variances. Adaptive modified maximum likelihood (AMML) estimators are used in developing the proposed tests since they are highly efficient under LTS distribution. An R package called RobustBF is given to show the implementation of these tests. Simulated Type I error rates …

Volesti: Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos

The R Journal

Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language.

Drhotnet: An R Package For Detecting Differential Risk Hotspots On A Linear Network, Álvaro Briz-Redón, Francisco Martínez-Ruiz, Francisco Montes

The R Journal

One of the most common applications of spatial data analysis is detecting zones, at a certain scale, where a point-referenced event under study is especially concentrated. The detection of such zones, which are usually referred to as hotspots, is essential in certain fields such as criminology, epidemiology, or traffic safety. Traditionally, hotspot detection procedures have been developed over areal units of analysis. Although working at this spatial scale can be suitable enough for many research or practical purposes, detecting hotspots at a more accurate level (for instance, at the road segment level) may be more convenient sometimes. Furthermore, it is …

Maint.Data: Modelling And Analysing Interval Data In R, A Pedro Duarte Silva, Paula Brito, Peter Filzmoser, José G. Dias

The R Journal

We present the CRAN R package MAINT.Data for the modelling and analysis of multivariate interval data, i.e., where units are described by variables whose values are intervals of R, representing intrinsic variability. Parametric inference methodologies based on probabilistic models for interval variables have been developed, where each interval is represented by its midpoint and log-range, for which multivariate Normal and Skew-Normal distributions are assumed. The intrinsic nature of the interval variables leads to special structures of the variance-covariance matrix, which are represented by four different possible configurations. MAINT.Data implements the proposed methodologies in the S4 object system, introducing a …

Matchthem: Matching And Weighting After Multiple Imputation, Farhad Pishgar, Noah Greifer, Clémence Leyrat, Elizabeth Stuart

The R Journal

Balancing the distributions of the confounders across the exposure levels in an observational study through matching or weighting is an accepted method to control for confounding due to these variables when estimating the association between an exposure and outcome and reducing the degree of dependence on certain modeling assumptions. Despite the increasing popularity in practice, these procedures cannot be immediately applied to datasets with missing values. Multiple imputation of the missing data is a popular approach to account for missing values while preserving the number of units in the dataset and accounting for the uncertainty in the missing values. However, …

Diproperm: An R Package For The Diproperm Test, Andrew G. Allmon, J.S. Marron, Michael G. Hudgens

The R Journal

High-dimensional low sample size (HDLSS) data sets frequently emerge in many biomedical applications. The direction-projection-permutation (DiProPerm) test is a two-sample hypothesis test for comparing two high-dimensional distributions. The DiProPerm test is exact, i.e., the type I error is guaranteed to be controlled at the nominal level for any sample size, and thus is applicable in the HDLSS setting. This paper discusses the key components of the DiProPerm test, introduces the diproperm R package, and demonstrates the package on a real-world data set

Bayessenmc: An R Package For Bayesian Sensitivity Analysis Of Misclassification, Jinhui Yang, Lifeng Lin, Haitao Chu

The R Journal

In case–control studies, the odds ratio is commonly used to summarize the association between a binary exposure and a dichotomous outcome. However, exposure misclassification frequently appears in case–control studies due to inaccurate data reporting, which can produce bias in measures of association. In this article, we implement a Bayesian sensitivity analysis of misclassification to provide a full posterior inference on the corrected odds ratio under both non-differential and differential misclassification. We present an R (R Core Team, 2018) package BayesSenMC, which provides user-friendly functions for its implementation. The usage is illustrated by a real data analysis on the association between …

Passo: An R Package For Assessing Partial Association Between Ordinal Variables, Shaobo Li, Xiaorui Zhu, Yuejie Chen, Dungang Liu

The R Journal

Partial association, the dependency between variables after adjusting for a set of covariates, is an important statistical notion for scientific research. However, if the variables of interest are ordered categorical data, the development of statistical methods and software for assessing their partial association is limited. Following the framework established by Liu et al. (2021), we develop an R package PAsso for assessing Partial Associations between ordinal variables. The package provides various functions that allow users to perform a wide spectrum of assessments, including quantification, visualization, and hypothesis testing. In this paper, we discuss the implementation of PAsso in …

Ngsseml: Non-Gaussian State Space With Exact Marginal Likelihood, Thiago R. Santos, Glaura C. Franco, Dani Gamerman

The R Journal

The number of packages/software for Gaussian State Space models has increased over recent decades. However, there are very few codes available for non-Gaussian State Space (NGSS) models due to analytical intractability that prevents exact calculations. One of the few tractable exceptions is the family of NGSS with exact marginal likelihood, named NGSSEML. In this work, we present the wide range of data formats and distributions handled by NGSSEML and a package in the R language to perform classical and Bayesian inference for them. Special functions for filtering, forecasting, and smoothing procedures and the exact calculation of the marginal likelihood function …

Dad: An R Package For Visualisation, Classification And Discrimination Of Multivariate Groups Modelled By Their Densities, Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard

The R Journal

Multidimensional scaling (MDS), hierarchical cluster analysis (HCA), and discriminant analysis (DA) are classical techniques which deal with data made of n individuals and p variables. When the individuals are divided into T groups, the R package dad associates with each group a multivariate probability density function and then carries out these techniques on the densities, which are estimated by the data under consideration. These techniques are based on distance measures between densities: chi-square, Hellinger, Jeffreys, Jensen-Shannon, and L^p for discrete densities, Hellinger , Jeffreys, L² , and 2-Wasserstein for Gaussian densities, and L² for numeric non-Gaussian densities …

Estimating Social Influence Effects In Networks Using A Latent Space Adjusted Approach In R, Ran Xu

The R Journal

Social influence effects have been extensively studied in various empirical network research. However, many challenges remain in estimating social influence effects in networks, as influence effects are often entangled with other factors, such as homophily in the selection process and the common social-environmental factors that individuals are embedded in. Methods currently available either do not solve these problems or require stringent assumptions. Recent works by Xu (2018) and others have shown that a latent space adjusted approach based on the latent space model has the potential to disentangle the influence effects from other processes, and the simulation evidence has shown …

G2f As A Novel Tool To Find And Fill Gaps In Metabolic Networks, Daniel Osorio, Kelly Botero, Andrés Pinzón Velasco, Nicolás Mendoza-Mejía, Felipe Rojas-Rodríguez, George Barreto, Janneth González

The R Journal

During the building of a genome-scale metabolic model, there are several dead-end metabolites and substrates which cannot be imported, produced, nor used by any reaction incorporated in the network. The presence of these dead-end metabolites can block out the net flux of the objective function when it is evaluated through Flux Balance Analysis (FBA), and when it is not blocked, bias in the biological conclusions increase. In this aspect, the refinement to restore the connectivity of the network can be carried out manually or using computational algorithms. The g2f package was designed as a tool to find the gaps from …

Rejoinder: Software Engineering And R Programming, Melina Vidoni

The R Journal

It is a pleasure to take part in such fruitful discussion about the relationship between Software Engineering and R programming, and what could be gain by allowing each to look more closely at the other. Several discussants make valuable arguments that ought to be further discussed

The R Quest: From Users To Developers, Simon Urbanek

The R Journal

R is not a programming language, and this produces the inherent dichotomy between analytics and software engineering. With the emergence of data science, the opportunity exists to bridge this gap, especially through teaching practices.

The R Developer Community Does Have A Strong Software Engineering Culture, Maëlle Salmon, Karthik Ram

The R Journal

There is a strong software engineering culture in the R developer community. We recommend creating, updating and vetting packages as well as keeping up with community standards. We invite contributions to the rOpenSci project, where participants can gain experience that will shape their work and that of their peers.

American Burying Beetle, Plant Richness, And Soil Property Responses To Collapse Of Juniperus Virginiana Woodlands With Fire, Alison K. Ludwig

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Grasslands are declining in the Great Plains due to land use changes, woody plant encroachment, and loss of historic fire cycles. Prescribed burn associations have utilized prescribed fire to collapse invading woodlands and allow the restoration of grasslands. This fire is considered “extreme” because it is capable of changing the structure and function of an ecosystem. Our study site is the Loess Canyons Experimental Landscape, a long-term, ecoregion-scale experiment to apply prescribed fire across the region to restore grasslands. The Nebraska Natural Legacy Project established the Loess Canyons ecoregion as a Biologically-Unique Landscape in 2005 with the state’s wildlife action …

Voltage Controlled Néel Vector Rotation In Zero Magnetic Field, Ather Mahmood, Will Echtenkamp, Mike Street, Jun Lei Wang, Shi Cao, Takashi Komesu, Peter Dowben, Pratyush Buragohain, Haidong Lu, Alexei Gruverman, Arun Parthasarathy, Shaloo Rakheja, Christian Binek

Peter Dowben Publications

Multi-functional thin films of boron (B) doped Cr₂O₃ exhibit voltage-controlled and nonvolatile Néel vector reorientation in the absence of an applied magnetic field, H. Toggling of antiferromagnetic states is demonstrated in prototype device structures at CMOS compatible temperatures between 300 and 400 K. The boundary magnetization associated with the Néel vector orientation serves as state variable which is read via magnetoresistive detection in a Pt Hall bar adjacent to the B:Cr₂O₃ film. Switching of the Hall voltage between zero and non-zero values implies Néel vector rotation by 90 degrees. Combined magnetometry, spin resolved inverse …

Comparative Analysis Of Kmer Counting And Estimation Tools, Ankitha Vejandla

School of Computing: Dissertations, Theses, and Student Research

The rapid development of next-generation sequencing (NGS) technologies for determining the sequence of DNA has revolutionized genome research in recent years. De novo assemblers are the most commonly used tools to perform genome assembly. Most of the assemblers use de Bruijn graphs that break the sequenced reads into smaller sequences (sub-strings), called kmers, where k denotes the length of the sub-strings. The kmer counting and analysis of kmer frequency distribution are important in genome assembly. The main goal of this research is to provide a detailed analysis of the performance of different kmer counting and estimation tools that are currently …

Agent Based Modeling Of The Spread Of Social Unrest Based On Infectious Disease Spread Model, Anup Adhikari

School of Computing: Dissertations, Theses, and Student Research

Social unrest activities are the tools for people to show dissatisfaction, and often people are motivated by similar unrest activities in another region. This causes a spread of unrest activities across space and time. In this thesis, we model the spread of social unrest across time and space. The underlying novel methodology is to model the regions as agents that transition from one state to another based on changes in their environment. The methodology involves (1) creating a region vector for each agent based on socio-demographic, cultural, economic, infrastructural, geographic, and environmental (SCEIGE) factors, (2) formulating neighborhood distance function to …

Algorithmic Trading And Market Quality: International Evidence, Ekkehart Boehmer, Kingsley Fong, Juan (Julie) Wu

Department of Finance: Faculty Publications

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use exchange co-location service that increases AT as an exogenous instrument to draw causal inferences of AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

Genome Annotation Using Average Mutual Information, Garin P. Newcomb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Advancements in high-throughput DNA sequencing technologies and ambitious goals for their use are resulting in the generation of a deluge of unannotated sequenced genomes. This makes computational tools that can aid in annotation increasingly valuable.

Here, we provide a detailed exploration of the utility as well as the limitations of average mutual information (AMI) in several steps of genome annotation. For a genomic sequence, AMI is a measure of the information a base contains about the base separated by a fixed lag. A profile is constructed by calculating AMI at multiple lags. In addition to traditional AMI, we employ two …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Deterring Non-Target Birds From Toxic Bait Sites For Wild Pigs, Nathan P. Snow, Joseph M. Halseth, Justin A. Foster, Michael J. Lavelle, Justin W. Fischer, Michael P. Glow, Ingrid A. Messer, Seth M. Cook, Kurt C. Vercauteren

United States Department of Agriculture Wildlife Services: Staff Publications

Toxic baiting of wild pigs (Sus scrofa) is a potential new tool for population control and damage reduction in the US. Field trials testing a prototype toxic bait (HOGGONE 2 containing 5% sodium nitrite [SN]), though, revealed that wild pigs spilled small particles of toxic bait outside of bait stations which subsequently created hazards for non-target species that consumed those particles, primarily passerine birds. To deter non-target birds from consuming particles of spilled bait, we tested four deterrents at mock bait sites (i.e., baited with bird seed) in north-central Colorado, USA during April–May 2020. We found a programable, inflatable deterrent …

Towards A More Comprehensive Understanding Of Wild Pig (Sus Scrofa) Impacts On Agricultural Producers: Insights From A Texas Case Study, Keith M. Carlisle, Nicole Didero, Sophie Mckee, Julie Elser, Stephanie A. Shwiff

United States Department of Agriculture Wildlife Services: Staff Publications

This research investigates the impacts of invasive wild pigs (Sus scrofa Linneaus) on agricultural producers in Texas, with the aim of identifying and describing all categories of wild pig impacts and quantifying the extent of producers’ over- or underestimation of their total wild pig-related costs in 2018, as compared to calculations based upon data subsequently provided by the producers about individual wild pig-related costs and losses. Based on interviews with 23 producers in 16 Texas counties, we identified more than 20 discrete categories of negative impacts and negligible positive impacts associated with wild pigs. Among them were categories that have …

Landscape Transformations Produce Favorable Roosting Conditions For Turkey Vultures And Black Vultures, Jacob E. Hill, Kenneth F. Kellner, Bryan M. Kluever, Michael L. Avery, John S. Humphrey, Eric A. Tillman, Travis L. Devault, Jerrold L. Belant

United States Department of Agriculture Wildlife Services: Staff Publications

Recent increases in turkey vulture (Cathartes aura) and black vulture (Coragyps atratus) populations in North America have been attributed in part to their success adapting to human-modified landscapes. However, the capacity for such landscapes to generate favorable roosting conditions for these species has not been thoroughly investigated. We assessed the role of anthropogenic and natural landscape elements on roosting habitat selection of 11 black and 7 turkey vultures in coastal South Carolina, USA using a GPS satellite transmitter dataset derived from previous research. Our dataset spanned 2006–2012 and contained data from 7916 nights of roosting. Landscape …

Reproductive Success Of Captive-Reared Allegheny Woodrats (Neotoma Magister) Released Into Genetically Depauperate Populations, Miracle M. Davis, Timothy J. Smyser, Scott A. Johnson, Joseph Duchamp, Jeffery L. Larkin, Robert K. Swihart, Jacqueline M. Doyle

United States Department of Agriculture Wildlife Services: Staff Publications

Habitat fragmentation and degradation have led to a proliferation of small and isolated populations that are vulnerable to genetic erosion. Reduction in habitat and concomitant declines in population connectivity can expediate the collapse of species that exist as natural metapopulations. In recent years, Allegheny woodrats (Neotoma magister) have experienced local extirpations and declines in genetic diversity across their range due to disease-related mortality, reduced food availability, and disruption of connectivity among subpopulations. In response, we developed a captive-breeding program to facilitate genetic management of isolated woodrat populations in Indiana. Between 2010 and 2012, 27 captive-reared individuals were released to four …

Economic Estimates Of Wild Hog (Sus Scrofa) Damage And Control Among Young Forest Plantations In Alabama, Micah Fern, Rebecca Barlow, Chris Slootmaker, John Kush, Stephanie Shwiff, Larry Teeter, Jim Armstrong

United States Department of Agriculture Wildlife Services: Staff Publications

Operating as ecological engineers, the increased distribution and abundance of wild hogs (Sus scrofa) has caused considerable socio-economic impacts. The international scope of economic research providing wild hog damage estimates are often confined to agricultural crops, while damage estimates among forest plantations are lacking. In Alabama, private landowners hold the majority of timberland acreage and are less equipped to absorb financial losses from wild hog damage than their industrial counterparts. A survey was conducted to estimate the economic impact of wild hogs, namely costs of damage and control, to privately owned forestlands. The survey was distributed in the …

Sex And Nest Type Influence Avian Blood Parasite Prevalence In A High-Elevation Bird Community, Marina D. Rodriguez, Paul F. Doherty, Antoinette J. Piaggio, Kathryn P. Huyvaert

United States Department of Agriculture Wildlife Services: Staff Publications

Background: The prevalence of avian haemosporidian parasites and the factors influencing infection in the Colorado Rocky Mountains are largely unknown. With climate change expected to promote the expansion of vector and avian blood parasite distributions, baseline knowledge and continued monitoring of the prevalence and diversity of these parasites is needed.

Methods: Using an occupancy modeling framework, we conducted a survey of haemosporidian parasite species infecting an avian community in the Colorado Rocky Mountains in order to estimate the prevalence and diversity of blood parasites and to investigate species-level and individual-level characteristics that may influence infection.

Results: We estimated the prevalence …