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Articles 1621 - 1650 of 26913
Full-Text Articles in Entire DC Network
Biclustermd: An R Package For Biclustering With Missing Values, John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen Vardeman, Jing Li
Biclustermd: An R Package For Biclustering With Missing Values, John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen Vardeman, Jing Li
The R Journal
Biclustering is a statistical learning technique that attempts to find homogeneous partitions of rows and columns of a data matrix. For example, movie ratings might be biclustered to group both raters and movies. biclust is a current R package allowing users to implement a variety of biclustering algorithms. However, its algorithms do not allow the data matrix to have missing values. We provide a new R package, biclustermd, which allows users to perform biclustering on numeric data even in the presence of missing values.
Modeling Regimes With Extremes: The Bayesdfa Package For Identifying And Forecasting Common Trends And Anomalies In Multivariate Time-Series Data, Eric J. Ward, Sean C. Anderson, Luis A. Damiano, Mary E. Hunsicker, Michael A. Litzow
Modeling Regimes With Extremes: The Bayesdfa Package For Identifying And Forecasting Common Trends And Anomalies In Multivariate Time-Series Data, Eric J. Ward, Sean C. Anderson, Luis A. Damiano, Mary E. Hunsicker, Michael A. Litzow
The R Journal
The bayesdfa package provides a flexible Bayesian modeling framework for applying dynamic factor analysis (DFA) to multivariate time-series data as a dimension reduction tool. The core estimation is done with the Stan probabilistic programming language. In addition to being one of the few Bayesian implementations of DFA, novel features of this model include (1) optionally modeling latent process deviations as drawn from a Student-t distribution to better model extremes, and (2) optionally including autoregressive and moving-average components in the latent trends. Besides estimation, we provide a series of plotting functions to visualize trends, loadings, and model predicted values. A secondary …
Ppci: An R Package For Cluster Identification Using Projection Pursuit, David P. Hofmeyr, Nicos G. Pavlidis
Ppci: An R Package For Cluster Identification Using Projection Pursuit, David P. Hofmeyr, Nicos G. Pavlidis
The R Journal
This paper presents the R package PPCI which implements three recently proposed projection pursuit methods for clustering. The methods are unified by the approach of defining an optimal hyperplane to separate clusters, and deriving a projection index whose optimiser is the vector normal to this separating hyperplane. Divisive hierarchical clustering algorithms that can detect clusters defined in different subspaces are readily obtained by recursively bi-partitioning the data through such hyperplanes. Projecting onto the vector normal to the optimal hyperplane enables visualisations of the data that can be used to validate the partition at each level of the cluster hierarchy. Clustering …
Coxed: An R Package For Computing Duration-Based Quantities From The Cox Proportional Hazards Model, Jonathan Kropko, Jeffrey J. Harden
Coxed: An R Package For Computing Duration-Based Quantities From The Cox Proportional Hazards Model, Jonathan Kropko, Jeffrey J. Harden
The R Journal
The Cox proportional hazards model is one of the most frequently used estimators in duration (survival) analysis. Because it is estimated using only the observed durations’ rank ordering, typical quantities of interest used to communicate results of the Cox model come from the hazard function (e.g., hazard ratios or percentage changes in the hazard rate). These quantities are substantively vague and difficult for many audiences of research to understand. We introduce a suite of methods in the R package coxed to address these problems. The package allows researchers to calculate duration-based quantities from Cox model results, such as the expected …
Orthodr: Semiparametric Dimension Reduction Via Orthogonality Constrained, Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, Xin Zhang
Orthodr: Semiparametric Dimension Reduction Via Orthogonality Constrained, Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, Xin Zhang
The R Journal
orthoDr is a package in R that solves dimension reduction problems using orthogonality constrained optimization approach. The package serves as a unified framework for many regression and survival analysis dimension reduction models that utilize semiparametric estimating equations. The main computational machinery of orthoDr is a first-order algorithm developed by Wen and Yin (2012) for optimization within the Stiefel manifold. We implement the algorithm through Rcpp and OpenMP for fast computation. In addition, we developed a general-purpose solver for such constrained problems with user-specified objective functions, which works as a drop-in version of optim(). The package also serves as a platform …
Using Web Services To Work With Geodata In R, Jan-Philipp Kolb
Using Web Services To Work With Geodata In R, Jan-Philipp Kolb
The R Journal
Through collaborative mapping, a massive amount of data is accessible. Many individuals contribute information each day. The growing amount of geodata is gathered by volunteers or obtained via crowd-sourcing. One outstanding example of this is the OpenStreetMap (OSM) Project which provides access to big data in geography. Another online mapping service that enables the integration of geodata into the analysis is Google Maps. The expanding content and the availability of geographic information radically changes the perspective on geodata (Chilton 2009). Recently many application programming interfaces (APIs) have been built on OSM and Google Maps. That leads to a point where …
Review Of Sky Dance Of The Woodcock: The Habits And Habitats Of A Strange Little Bird, By Greg Hoch, David E. Andersen
Review Of Sky Dance Of The Woodcock: The Habits And Habitats Of A Strange Little Bird, By Greg Hoch, David E. Andersen
The Prairie Naturalist
American Woodcock (Scolopax minor) have enthralled conservationists (including Aldo Leopold), bird watchers, wildlife enthusiasts, hunters, and others interested in the natural world for centuries. No doubt, woodcock also have enthralled humans in North America for millennia prior to written descriptions of the woodcock’s courtship displays, habitat preferences, and curious behavior and anatomy. As perhaps the most extensively studied species of shorebird in the world, there is a rich and extensive literature, both scientific and popular, focused on woodcock ecology, behavior, and hunting. To that extensive body of literature, Sky Dance of the Woodcock provides an updated summary of …
Serological Survey And Pathogen Exposure Of Adult Female White-Tailed Deer In The Western Dakotas, Katherine L. Moratz, Bailey S. Gullikson, Eric S. Michel, Daniel M. Grove, Jonathan A. Jenks, William Jensen
Serological Survey And Pathogen Exposure Of Adult Female White-Tailed Deer In The Western Dakotas, Katherine L. Moratz, Bailey S. Gullikson, Eric S. Michel, Daniel M. Grove, Jonathan A. Jenks, William Jensen
The Prairie Naturalist
Establishing baseline values for pathogen exposure and nutritional indices is necessary to monitor population health. However, little is known about white-tailed deer (Odocoileus virginianus) pathogen exposure and nutritional condition in the Northern Great Plains. Our objective was to assess pathogen exposure and establish nutritional indices for female white-tailed deer in Dunn and Grant counties, North Dakota and Perkins County, South Dakota. During 2014, we collected blood serum from 150 adult female white-tailed deer. Pathogens with the highest antibody prevalence included West Nile Virus (WNV; 85%), epizootic hemorrhagic disease (48%), and malignant catarrhal fever (32%). Serum values for creatine …
Spgarch: An R-Package For Spatial And Spatiotemporal Arch And Garch Models, Philipp Otto
Spgarch: An R-Package For Spatial And Spatiotemporal Arch And Garch Models, Philipp Otto
The R Journal
In this paper, a general overview on spatial and spatiotemporal ARCH models is provided. In particular, we distinguish between three different spatial ARCH-type models. In addition to the original definition of Otto et al. (2016), we introduce an logarithmic spatial ARCH model in this paper. For this new model, maximum-likelihood estimators for the parameters are proposed. In addition, we consider a new complex-valued definition of the spatial ARCH process. Moreover, spatial GARCH models are briefly discussed. From a practical point of view, the use of the R-package spGARCH is demonstrated. To be precise, we show how the proposed spatial ARCH …
Hcmodelsets: An R Package For Specifying Sets Of Well-Fitting Models In High Dimensions, Henrique Hoeltgebaum, Heather Battey
Hcmodelsets: An R Package For Specifying Sets Of Well-Fitting Models In High Dimensions, Henrique Hoeltgebaum, Heather Battey
The R Journal
In the context of regression with a large number of explanatory variables, Cox and Battey (2017) emphasize that if there are alternative reasonable explanations of the data that are statistically indistinguishable, one should aim to specify as many of these explanations as is feasible. The standard practice, by contrast, is to report a single effective model for prediction. This paper illustrates the R implementation of the new ideas in the package HCmodelSets, using simple reproducible examples and real data. Results of some simulation experiments are also reported.
The R Package Trafo For Transforming Linear Regression Models, Lily Medina, Ann-Kristin Kreutzmann, Natalia Rojas-Perilla, Piedad Castro
The R Package Trafo For Transforming Linear Regression Models, Lily Medina, Ann-Kristin Kreutzmann, Natalia Rojas-Perilla, Piedad Castro
The R Journal
Researchers and data-analysts often use the linear regression model for descriptive, predictive, and inferential purposes. This model relies on a set of assumptions that, when not satisfied, yields biased results and noisy estimates. A common problem that can be solved in many ways – use of less restrictive methods (e.g. generalized linear regression models or non-parametric methods ), variance corrections or transformations of the response variable just to name a few. We focus on the latter option as it allows to keep using the simple and well-known linear regression model. The list of transformations proposed in the literature is long …
Comparing Namedcapture With Other R Packages For Regular Expressions, Toby Dylan Hocking
Comparing Namedcapture With Other R Packages For Regular Expressions, Toby Dylan Hocking
The R Journal
Regular expressions are powerful tools for manipulating non-tabular textual data. For many tasks (visualization, machine learning, etc), tables of numbers must be extracted from such data before processing by other R functions. We present the R package namedCapture, which facilitates such tasks by providing a new user-friendly syntax for defining regular expressions in R code. We begin by describing the history of regular expressions and their usage in R. We then describe the new features of the namedCapture package, and provide detailed comparisons with related R packages (rex, stringr, stringi, tidyr, rematch2, re2r).
News From The Bioconductor Project, Bioconductor Core Team
News From The Bioconductor Project, Bioconductor Core Team
The R Journal
The Bioconductor project provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.10 was released on 30 October, 2019. It is compatible with R 3.6.1 and consists of 1823 software packages, 384 experiment data packages, 953 up-to-date annotation packages, and 27 workflows. The release announcement includes descriptions of 94 new software packages, and updated NEWS files for many additional packages. Start using Bioconductor by installing the most recent version of R and evaluating the commands
Fitting Tails By The Empirical Residual Coefficient Of Variation: The Ercv Package, Joan Del Castillo, Isabel Serra, Maria Padilla, David Moriña
Fitting Tails By The Empirical Residual Coefficient Of Variation: The Ercv Package, Joan Del Castillo, Isabel Serra, Maria Padilla, David Moriña
The R Journal
This article is a self-contained introduction to the R package ercv and to the methodology on which it is based through the analysis of nine examples. The methodology is simple and trustworthy for the analysis of extreme values and relates the two main existing methodologies. The package contains R functions for visualizing, fitting and validating the distribution of tails. It also provides multiple threshold tests for a generalized Pareto distribution, together with an automatic threshold selection algorithm.
Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis
Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis
The R Journal
In the past 4 months, 632 new packages were added to the CRAN package repository. 27 packages were unarchived and 182 were archived. The following shows the growth of the number of active packages in the CRAN package repository:
Rollmatch: An R Package For Rolling Entry Matching, Kasey Jones, Rob Chew, Allison Witman, Yiyan Liu
Rollmatch: An R Package For Rolling Entry Matching, Kasey Jones, Rob Chew, Allison Witman, Yiyan Liu
The R Journal
The gold standard of experimental research is the randomized control trial. However, interventions are often implemented without a randomized control group for practical or ethical reasons. Propensity score matching (PSM) is a popular method for minimizing the effects of a randomized experiment from observational data by matching members of a treatment group to similar candidates that did not receive the intervention. Traditional PSM is not designed for studies that enroll participants on a rolling basis and does not provide a solution for interventions in which the baseline and intervention period are undefined in the comparison group. Rolling Entry Matching (REM) …
Editorial, Michael J. Kane
Editorial, Michael J. Kane
The R Journal
On behalf of the editorial board, I am pleased to present Volume 11, Issue 2 of the R Journal and my first issue as the Editor in Chief. This year, both Colin Gillespie and Catherine Healey join the Editorial Board, and Norm Matloff will rotate out. The R Journal continues to see increases in impact and popularity and this year we plan on making advances to better serve the community and streamline the publishing process to meet the increase in submissions we have seen over the last few years.
Dr4pl: A Stable Convergence Algorithm For The 4 Parameter Logistic Model, Hyowon An, Justin T. Landis, Aubrey G. Bailey, James S. Marron, Dirk P. Dittmer
Dr4pl: A Stable Convergence Algorithm For The 4 Parameter Logistic Model, Hyowon An, Justin T. Landis, Aubrey G. Bailey, James S. Marron, Dirk P. Dittmer
The R Journal
The 4 Parameter Logistic (4PL) model has been recognized as a major tool to analyze the relationship between doses and responses in pharmacological experiments. A main strength of this model is that each parameter contributes an intuitive meaning enhancing interpretability of a fitted model. However, implementing the 4PL model using conventional statistical software often encounters numerical errors. This paper highlights the issue of convergence failure and presents several causes with solutions. These causes include outliers and a non-logistic data shape, so useful remedies such as robust estimation, outlier diagnostics and constrained optimization are proposed. These features are implemented in a …
Associative Classification In R: Arc, Arulescba, And Rcba, Michael Hahsler, Ian Johnson, Tomáš Kliegr, Jaroslav Kuchař
Associative Classification In R: Arc, Arulescba, And Rcba, Michael Hahsler, Ian Johnson, Tomáš Kliegr, Jaroslav Kuchař
The R Journal
Several methods for creating classifiers based on rules discovered via association rule mining have been proposed in the literature. These classifiers are called associative classifiers and the best-known algorithm is Classification Based on Associations (CBA). Interestingly, only very few implementations are available and, until recently, no implementation was available for R. Now, three packages provide CBA. This paper introduces associative classification, the CBA algorithm, and how it can be used in R. A comparison of the three packages is provided to give the potential user an idea about the advantages of each of the implementations. We also show how the …
Convergenceclubs: A Package For Performing The Phillips And Sul's Club Convergence Clustering Procedure, Roberto Sichera, Pietro Pizzuto
Convergenceclubs: A Package For Performing The Phillips And Sul's Club Convergence Clustering Procedure, Roberto Sichera, Pietro Pizzuto
The R Journal
This paper introduces package ConvergenceClubs, which implements functions to perform the Phillips and Sul (2007, 2009) club convergence clustering procedure in a simple and reproducible manner. The approach proposed by Phillips and Sul to analyse the convergence patterns of groups of economies is formulated as a nonlinear time varying factor model that allows for different time paths as well as individual heterogeneity. Unlike other approaches in which economies are grouped a priori, it also allows the endogenous determination of convergence clubs. The algorithm, usage, and implementation details are discussed.
R News, R Core Team
R News, R Core Team
The R Journal
CHANGES IN R 3.6.2
CHANGES IN R 3.6.0
CHANGES IN R 3.5.3
CHANGES IN R 3.5.2
CHANGES IN R 3.5.1
CHANGES IN R 3.5.0
CHANGES IN R 3.4.4
CHANGES IN R 3.4.3
CHANGES IN R 3.4.2
CHANGES IN R 3.4.1
CHANGES IN R 3.4.0
CHANGES IN R 3.3.3
CHANGES IN R 3.3.2
CHANGES IN R 3.3.1
CHANGES IN R 3.3.0
CHANGES IN R 3.2.5
CHANGES IN R 3.2.4
CHANGES IN R 3.2.3
CHANGES IN R 3.2.2
CHANGES IN R 3.2.1
CHANGES IN R 3.2.0
CHANGES IN R 3.1.3
CHANGES IN R 3.1.2
CHANGES IN R 3.1.1
CHANGES IN R 3.1.0 …
The Idspatialstats R Package: Quantifying Spatial Dependence Of Infectious Disease Spread, John R. Giles, Henrik Salje, Justin Lessler
The Idspatialstats R Package: Quantifying Spatial Dependence Of Infectious Disease Spread, John R. Giles, Henrik Salje, Justin Lessler
The R Journal
Spatial statistics for infectious diseases are important because the spatial and temporal scale over which transmission operates determine the dynamics of disease spread. Many methods for quantifying the distribution and clustering of spatial point patterns have been developed (e.g. K-function and pair correlation function) and are routinely applied to infectious disease case occurrence data. However, these methods do not explicitly account for overlapping chains of transmission and require knowledge of the underlying population distribution, which can be limiting when analyzing epidemic case occurrence data. Therefore, we developed two novel spatial statistics that account for these effects to estimate: 1) …
Time Series Forecasting With Knn In R: The Tsfknn Package, Francisco Martínez, María P. Frías, Francisco Charte, Antonio J. Rivera
Time Series Forecasting With Knn In R: The Tsfknn Package, Francisco Martínez, María P. Frías, Francisco Charte, Antonio J. Rivera
The R Journal
In this paper the tsfknn package for time series forecasting using k-nearest neighbor regression is described. This package allows users to specify a KNN model and to generate its forecasts. The user can choose among different multi-step ahead strategies and among different functions to aggregate the targets of the nearest neighbors. It is also possible to assess the forecast accuracy of the KNN model.
Bondvaluation: An R Package For Fixed Coupon Bond Analysis, Wadim Djatschenko
Bondvaluation: An R Package For Fixed Coupon Bond Analysis, Wadim Djatschenko
The R Journal
t The purpose of this paper is to introduce the R package BondValuation for the analysis of large datasets of fixed coupon bonds. The conceptual heterogeneity of fixed coupon bonds traded in the global markets imposes a high degree of complexity on their comparative analysis. Contrary to baseline fixed income theory, in practice, most bonds feature coupon period irregularities. In addition, there are a multitude of day count methods that determine the interest accrual, the cash flows and the discount factors used in bond valuation. Several R packages, e.g., fBonds, RQuantLib, and YieldCurve, provide tools for fixed income analysis. Nevertheless, …
Recent Observations Of Water Shrews In Northeastern South Dakota, Dennis Skadsen, Robert M. Timm
Recent Observations Of Water Shrews In Northeastern South Dakota, Dennis Skadsen, Robert M. Timm
The Prairie Naturalist
North American water shrews in the genus Sorex are a complex of at least five species, three of which were recognized historically, Sorex alasksans, S. bendirii, and S. palustris (Hall 1981). Within what was previously considered the single, widespread northern species, S. palustris, two additional species are now recognized, S. albibarbis in the eastern US and Canada and S. navigator in the western United States and Canada (Hope et al. 2014; Nagorsen et al. 2017; Woodman 2018). The American water shrew (Sorex palustris) originally was documented in South Dakota by three females, two were collected 1876 and …
Final Thoughts As Editor-In-Chief, Christopher N. Jacques
Final Thoughts As Editor-In-Chief, Christopher N. Jacques
The Prairie Naturalist
Greetings GPNSS members! I write this editorial during a time of reflection as Editor-in-Chief of The Prairie Naturalist (TPN), and during unprecedented times as the global COVID-19 pandemic continues. In full disclosure, I do not have a particular topic for this editorial, other than to offer a few final thoughts as my time serving the Great Plains Natural Science Society and TPN.
Bats Of The Loess Hills Ecoregion Of Southeast Nebraska, Virgil Brack Jr, Dale W. Sparks, Darwin C. Brack
Bats Of The Loess Hills Ecoregion Of Southeast Nebraska, Virgil Brack Jr, Dale W. Sparks, Darwin C. Brack
The Prairie Naturalist
We surveyed bats at 49 sites in the Loess Hills Ecoregion of southeastern Nebraska, along the western edge of the eastern forest biome in eastern Richardson, Nemaha, and Otoe counties. We completed this study shortly before the northern long-eared bat (Myotis septentrionalis) was listed by the United States Fish and Wildlife Service under the Endangered Species Act. The expectation of listing, along with potential presence of the endangered Indiana bat (Myotis sodalis), motivated the study. We captured 183 bats of five species: eastern red bat (Lasiurus borealis) (n = 103; 56 %), big brown …
Reading Fluency And Gonoodle© Brain Breaks Among Elementary-Aged Children, Hannah Jeanne Wold
Reading Fluency And Gonoodle© Brain Breaks Among Elementary-Aged Children, Hannah Jeanne Wold
Theses and Dissertations
This study examines the immediate and chronic effects of physical activity (PA) breaks on reading fluency. While many teachers recognize the value of PA for increasing engagement and focus (getting the wiggles out) in academic endeavors, these results reveal increases in academic achievement in reading fluency are also possible.This study examines 384 second and third grade students with low income backgrounds from the Rocky Mountain region. A two-way analysis of variance (ANOVA) was used to examine the effects of chronic and acute brain breaks via GoNoodle© (McQuigg, 2013) on reading fluency and physical activity (steps). Between group differences were further …
Splice Performance Of #6 Reinforcing Bars In Masonry With Self-Consolidating Grout, Annie Ruth Nielson
Splice Performance Of #6 Reinforcing Bars In Masonry With Self-Consolidating Grout, Annie Ruth Nielson
Theses and Dissertations
Reinforced masonry grouted using self-consolidating grout (SCG) is a relatively new and economically competitive option for construction, providing advantages such as reduced construction time, decreased noise and vibration, and reliable consolidation. However, SCG has different properties than conventional grout and its performance should be verified using current governing code requirements. The purpose of this research program was to determine the development length of spliced reinforcing bars in masonry grouted with SCG.Twelve masonry panels, four courses high and two and a half blocks wide, were constructed using 8-inch concrete masonry units, each with two pairs of vertically spliced #6 reinforcing bars. …
Contextual Factors In Early Career Teaching: A Systematic Review Of International Research On Teacher Induction And Mentoring Programs, Benjamin Kutsyuruba, Keith D. Walker, Lorraine Godden
Contextual Factors In Early Career Teaching: A Systematic Review Of International Research On Teacher Induction And Mentoring Programs, Benjamin Kutsyuruba, Keith D. Walker, Lorraine Godden
Journal of Global Education and Research
Early career teachers (ECTs) are situated in a dynamic contextual landscape that both influences their development and practice and dictates professional expectations for instruction and professional learning. This systematic review of international research literature sought to establish the understanding of teacher induction and mentoring program support of ECTs through the following research questions: 1) which nations and regions are represented in research literature that details formal or programmatic support of ECTs? 2) what international research evidence is there to describe various contextual factors that affect experiences of ECTs? and, 3) how do teacher induction and mentorship programs respond to the …