Changes On Cran,
2020
WU Wirtschaftsuniversität Wien
Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis
The R Journal
In the past 4 months, 818 new packages were added to the CRAN package repository. 100 packages were archived and 248 were archived. The following shows the growth of the number of active packages in the CRAN package repository
R Foundation News,
2020
Universität Zürich
R Foundation News, Torsten Hothorn
The R Journal
Membership fees and donations received between 2020-09-09 and 2021-01-28.
Rngforgpd: An R Package For Generation Of Univariate And Multivariate Generalized Poisson Data,
2020
University of Illinois at Chicago
Rngforgpd: An R Package For Generation Of Univariate And Multivariate Generalized Poisson Data, Hesen Li, Hakan Demirtas, Ruizhe Chen
The R Journal
This article describes the R package RNGforGPD, which is designed for the generation of univariate and multivariate generalized Poisson data. Some illustrative examples are given, the utility and functionality of the package are demonstrated; and its performance is assessed via simulations that are devised around both artificial and real data.
Species Distribution Modeling Using Spatial Point Processes: A Case Study Of Sloth Occurrence In Costa Rica,
2020
King Abdullah University of Science and Technology
Species Distribution Modeling Using Spatial Point Processes: A Case Study Of Sloth Occurrence In Costa Rica, Paula Moraga
The R Journal
Species distribution models are widely used in ecology for conservation management of species and their environments. This paper demonstrates how to fit a log-Gaussian Cox process model to predict the intensity of sloth occurrence in Costa Rica, and assess the effect of climatic factors on spatial patterns using the R-INLA package. Species occurrence data are retrieved using spocc, and spatial climatic variables are obtained with raster. Spatial data and results are manipulated and visualized by means of several packages such as raster and tmap. This paper provides an accessible illustration of spatial point process modeling that can …
Tulip: A Toolbox For Linear Discriminant Analysis With Penalties,
2020
Florida State University
Tulip: A Toolbox For Linear Discriminant Analysis With Penalties, Yuqing Pan, Qing Mai, Xin Zhang
The R Journal
Linear discriminant analysis (LDA) is a powerful tool in building classifiers with easy computation and interpretation. Recent advancements in science technology have led to the popularity of datasets with high dimensions, high orders and complicated structure. Such datasetes motivate the generalization of LDA in various research directions. The R package TULIP integrates several popular high-dimensional LDA-based methods and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification. Functions are included for model fitting, cross validation and prediction. In addition, motivated by datasets with diverse sources of predictors, we further include functions for covariate adjustment. Our package is …
Testing The Equality Of Normal Distributed And Independent Groups’ Means Under Unequal Variances By Doex Package,
2020
Eskisehir Technical University
Testing The Equality Of Normal Distributed And Independent Groups’ Means Under Unequal Variances By Doex Package, Mustafa Cavus, Berna Yazıcı
The R Journal
In this paper, we present the doex package contains the tests for equality of normal distributed and independent group means under unequal variances such as Cochran F, Welch-Aspin, Welch, Box, Scott-Smith, Brown-Forsythe, Johansen F, Approximate F, Alexander-Govern, Generalized F, Modified Brown-Forsythe, Permutation F, Adjusted Welch, B2, Parametric Bootstrap, Fiducial Approach, and Alvandi Generalized F-test. Most of these tests are not available in any package. Thus, doex is easy to use for researchers in multidisciplinary studies. In this study, an extensive Monte-Carlo simulation study is conducted to investigate the performance of the the tests for equality of normal distributed group means …
News From The Bioconductor Project,
2020
University of Nebraska - Lincoln
News From The Bioconductor Project, Bioconductor Core Team
The R Journal
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.12 was released on 28 October, 2020. It is compatible with R 4.0.3 and consists of 1974 software packages, 398 experiment data packages, 968 up-to-date annotation packages, and 28 workflows. Books are a new addition, built regularly from source and therefore fully reproducible; an example is the community-developed Orchestrating Single-Cell Analysis with Bioconductor.
Kuhn-Tucker And Multiple Discrete-Continuous Extreme Value Model Estimation And Simulation In R: The Rmdcev Package,
2020
University of Saskatchewan
Kuhn-Tucker And Multiple Discrete-Continuous Extreme Value Model Estimation And Simulation In R: The Rmdcev Package, Patrick Lloyd-Smith
The R Journal
This paper introduces the package rmdcev in R for estimation and simulation of KuhnTucker demand models with individual heterogeneity. The models supported by rmdcev are the multiple-discrete continuous extreme value (MDCEV) model and Kuhn-Tucker specification common in the environmental economics literature on recreation demand. Latent class and random parameters specifications can be implemented and the models are fit using maximum likelihood estimation or Bayesian estimation. The rmdcev package also implements demand forecasting and welfare calculation for policy simulation. The purpose of this paper is to describe the model estimation and simulation framework and to demonstrate the functionalities of rmdcev using …
A Unified Algorithm For The Non-Convex Penalized Estimation: The Ncpen Package,
2020
Pepperdine University
A Unified Algorithm For The Non-Convex Penalized Estimation: The Ncpen Package, Dongshin Kim, Sangin Lee, Sunghoon Kwon
The R Journal
Various R packages have been developed for the non-convex penalized estimation but they can only be applied to the smoothly clipped absolute deviation (SCAD) or minimax concave penalty (MCP). We develop an R package, entitled ncpen, for the non-convex penalized estimation in order to make data analysts to experience other non-convex penalties. The package ncpen implements a unified algorithm based on the convex concave procedure and modified local quadratic approximation algorithm, which can be applied to a broader range of non-convex penalties, including the SCAD and MCP as special examples. Many user-friendly functionalities such as generalized information criteria, cross-validation …
User-Specified General-To-Specific And Indicator Saturation Methods,
2020
BI Norwegian Business School
User-Specified General-To-Specific And Indicator Saturation Methods, Genaro Sucarrat
The R Journal
General-to-Specific (GETS) modelling provides a comprehensive, systematic and cumulative approach to modelling that is ideally suited for conditional forecasting and counterfactual analysis, whereas Indicator Saturation (ISAT) is a powerful and flexible approach to the detection and estimation of structural breaks (e.g. changes in parameters), and to the detection of outliers. To these ends, multi path backwards elimination, single and multiple hypothesis tests on the coefficients, diagnostics tests andgoodness-of-fit measures are combined to produce a parsimonious final model. In many situations a specific model or estimator is needed, a specific set of diagnostics tests may be required, or a specific f …
Editorial,
2020
Yale University
Editorial, Michael J. Kane
The R Journal
On behalf of the editorial board, I am pleased to present Volume 12 Issue 2 of the R Journal. This is my third and final issue as the Editor-in-Chief. In the last year, we have made some substantial changes to the journal that I believe will continue to increase our capacity to support the growing data science and computational statistics communities, and continue to raise the visibility of the journal. In the last few months we recruited 10 Associate Editors and we are continuing the recruitment process. I’d like to publicly welcome our new Associate Editors, and thank each of …
Openland: Software For Quantitative Analysis And Visualization Of Land Use And Cover Change,
2020
Federal University of Mato Grosso
Openland: Software For Quantitative Analysis And Visualization Of Land Use And Cover Change, Reginal Exavier, Peter Zeilhofer
The R Journal
There is an increasing availability of spatially explicit, freely available land use and cover (LUC) time series worldwide. Because of the enormous amount of data this represents, the continuous updates and improvements in spatial and temporal resolution and category differentiation, as well as increasingly dynamic and complex changes made, manual data extraction and analysis is highly time consuming, and making software tools available to automatize LUC data assessment is becoming imperative. This paper presents a software developed in R, which combines LUC raster time series data and their transitions, calculates state-of-the-art LUC change indicators, and creates spatio-temporal visualizations, all in …
E-Rum2020: How We Turned A Physical Conference Into A Successful Virtual Event,
2020
Vanlog
E-Rum2020: How We Turned A Physical Conference Into A Successful Virtual Event, Mariachiara Fortuna, Francesca Vitalini, Mirko Signorelli, Emanuela Furfaro, Federico Marini, Gert Janssenswillen, Riccardo Porreca, Riccardo L. Rossi, Andrea Guzzo, Roberta Sirovich, Andrea Melloncelli, Lorenzo Salvi, Serena Signorelli, Filippo Chiarello
The R Journal
The European R Users Meeting 2020 (e-Rum2020) was a conference that was held virtually in June 2020. Originally, e-Rum2020 had been planned as a physical event to be held in Milano. However, the spread of the COVID-19 pandemic and the declaration of a nationwide lockdown induced the Organizing Committee to fully rethink the event, and to turn it into a live virtual conference. In this article, we describe the challenges that we encountered during the organization of e-Rum2020, and how wereacted to them. In doing so, we aim to provide future conference organizers with useful information on how to organize …
Miwqs: Multiple Imputation Using Weighted Quantile Sum Regression,
2020
Virginia Commonwealth University
Miwqs: Multiple Imputation Using Weighted Quantile Sum Regression, Paul M. Hargarten, David C. Wheeler
The R Journal
The miWQS package in the Comprehensive R Archive Network (CRAN) utilizes weighted quantile sum regression (WQS) in the multiple imputation (MI) framework. The data analyzed is a set/mixture of continuous and correlated components/chemicals that are reasonable to combine in an index and share a common outcome. These components are also interval-censored between zero and upper thresholds, or detection limits, which may differ among the components. This type of data is found in areas such as chemical epidemiological studies, sociology, and genomics. The miWQS package can be run using complete or incomplete data, which may be placed in the first quantile, …
News From The Forwards Taskforce,
2020
University of Warwick
News From The Forwards Taskforce, Heather Turner
The R Journal
Forwards is an R Foundation taskforce working to widen the participation of under represented groups in the R project and in related activities, such as the useR! conference. This report rounds up activities of the taskforce during the second half of 2020.
Farmtest: An R Package For Factor-Adjusted Robust Multiple Testing,
2020
Princeton University
Farmtest: An R Package For Factor-Adjusted Robust Multiple Testing, Koushiki Bose, Jianqing Fan, Yuan Ke, Xiaoou Pan, Wen-Xin Zhou
The R Journal
We provide a publicly available library FarmTest in the R programming system. This library implements a factor-adjusted robust multiple testing principle proposed by Fan et al. (2019) for large-scale simultaneous inference on mean effects. We use a multi-factor model to explicitly capture the dependence among a large pool of variables. Three types of factors are considered: observable, latent, and a mixture of observable and latent factors. The non-factor case, which corresponds to standard multiple mean testing under weak dependence, is also included. The library implements a series of adaptive Huber methods integrated with fast data-driven tuning schemes to estimate model …
A Bert-Based Dual Embedding Model For Chinese Idiom Prediction,
2020
Singapore Management University
A Bert-Based Dual Embedding Model For Chinese Idiom Prediction, Minghuan Tan, Jing Jiang
Research Collection School Of Computing and Information Systems
Chinese idioms are special fixed phrases usually derived from ancient stories, whose meanings are oftentimes highly idiomatic and non-compositional. The Chinese idiom prediction task is to select the correct idiom from a set of candidate idioms given a context with a blank. We propose a BERT-based dual embedding model to encode the contextual words as well as to learn dual embeddings of the idioms. Specifically, we first match the embedding of each candidate idiom with the hidden representation corresponding to the blank in the context. We then match the embedding of each candidate idiom with the hidden representations of all …
Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation,
2020
University of Arkansas, Fayetteville
Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation, Joseph Winstead Sirrianni
Graduate Theses and Dissertations
Cyber argumentation platforms implement theoretical argumentation structures that promote higher quality argumentation and allow for informative analysis of the discussions. Dr. Liu’s research group has designed and implemented a unique platform called the Intelligent Cyber Argumentation System (ICAS). ICAS structures its discussions into a weighted cyber argumentation graph, which describes the relationships between the different users, their posts in a discussion, the discussion topic, and the various subtopics in a discussion. This platform is unique as it encodes online discussions into weighted cyber argumentation graphs based on the user’s stances toward one another’s arguments and ideas. The resulting weighted cyber …
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences,
2020
Oakland University
Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi Khatchadourian
Publications and Research
Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices, …
Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia,
2020
Tijuana Institute of Technology, Mexico
Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia, Paul Valle
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
