Collaborative Software Development Using R-Forge
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Tinn-R Team Has a New Member Working on the Source Code: Wel- Come Huashan Chen
Editus eBook Series Editus eBooks is a series of electronic books aimed at students and re- searchers of arts and sciences in general. Tinn-R Editor (2010 1. ed. Rmetrics) Tinn-R Editor - GUI forR Language and Environment (2014 2. ed. Editus) José Cláudio Faria Philippe Grosjean Enio Galinkin Jelihovschi Ricardo Pietrobon Philipe Silva Farias Universidade Estadual de Santa Cruz GOVERNO DO ESTADO DA BAHIA JAQUES WAGNER - GOVERNADOR SECRETARIA DE EDUCAÇÃO OSVALDO BARRETO FILHO - SECRETÁRIO UNIVERSIDADE ESTADUAL DE SANTA CRUZ ADÉLIA MARIA CARVALHO DE MELO PINHEIRO - REITORA EVANDRO SENA FREIRE - VICE-REITOR DIRETORA DA EDITUS RITA VIRGINIA ALVES SANTOS ARGOLLO Conselho Editorial: Rita Virginia Alves Santos Argollo – Presidente Andréa de Azevedo Morégula André Luiz Rosa Ribeiro Adriana dos Santos Reis Lemos Dorival de Freitas Evandro Sena Freire Francisco Mendes Costa José Montival Alencar Junior Lurdes Bertol Rocha Maria Laura de Oliveira Gomes Marileide dos Santos de Oliveira Raimunda Alves Moreira de Assis Roseanne Montargil Rocha Silvia Maria Santos Carvalho Copyright©2015 by JOSÉ CLÁUDIO FARIA PHILIPPE GROSJEAN ENIO GALINKIN JELIHOVSCHI RICARDO PIETROBON PHILIPE SILVA FARIAS Direitos desta edição reservados à EDITUS - EDITORA DA UESC A reprodução não autorizada desta publicação, por qualquer meio, seja total ou parcial, constitui violação da Lei nº 9.610/98. Depósito legal na Biblioteca Nacional, conforme Lei nº 10.994, de 14 de dezembro de 2004. CAPA Carolina Sartório Faria REVISÃO Amek Traduções Dados Internacionais de Catalogação na Publicação (CIP) T591 Tinn-R Editor – GUI for R Language and Environment / José Cláudio Faria [et al.]. – 2. ed. – Ilhéus, BA : Editus, 2015. xvii, 279 p. ; pdf Texto em inglês. -
Navigating the R Package Universe by Julia Silge, John C
CONTRIBUTED RESEARCH ARTICLES 558 Navigating the R Package Universe by Julia Silge, John C. Nash, and Spencer Graves Abstract Today, the enormous number of contributed packages available to R users outstrips any given user’s ability to understand how these packages work, their relative merits, or how they are related to each other. We organized a plenary session at useR!2017 in Brussels for the R community to think through these issues and ways forward. This session considered three key points of discussion. Users can navigate the universe of R packages with (1) capabilities for directly searching for R packages, (2) guidance for which packages to use, e.g., from CRAN Task Views and other sources, and (3) access to common interfaces for alternative approaches to essentially the same problem. Introduction As of our writing, there are over 13,000 packages on CRAN. R users must approach this abundance of packages with effective strategies to find what they need and choose which packages to invest time in learning how to use. At useR!2017 in Brussels, we organized a plenary session on this issue, with three themes: search, guidance, and unification. Here, we summarize these important themes, the discussion in our community both at useR!2017 and in the intervening months, and where we can go from here. Users need options to search R packages, perhaps the content of DESCRIPTION files, documenta- tion files, or other components of R packages. One author (SG) has worked on the issue of searching for R functions from within R itself in the sos package (Graves et al., 2017). -
Supplementary Materials
Tomic et al, SIMON, an automated machine learning system reveals immune signatures of influenza vaccine responses 1 Supplementary Materials: 2 3 Figure S1. Staining profiles and gating scheme of immune cell subsets analyzed using mass 4 cytometry. Representative gating strategy for phenotype analysis of different blood- 5 derived immune cell subsets analyzed using mass cytometry in the sample from one donor 6 acquired before vaccination. In total PBMC from healthy 187 donors were analyzed using 7 same gating scheme. Text above plots indicates parent population, while arrows show 8 gating strategy defining major immune cell subsets (CD4+ T cells, CD8+ T cells, B cells, 9 NK cells, Tregs, NKT cells, etc.). 10 2 11 12 Figure S2. Distribution of high and low responders included in the initial dataset. Distribution 13 of individuals in groups of high (red, n=64) and low (grey, n=123) responders regarding the 14 (A) CMV status, gender and study year. (B) Age distribution between high and low 15 responders. Age is indicated in years. 16 3 17 18 Figure S3. Assays performed across different clinical studies and study years. Data from 5 19 different clinical studies (Study 15, 17, 18, 21 and 29) were included in the analysis. Flow 20 cytometry was performed only in year 2009, in other years phenotype of immune cells was 21 determined by mass cytometry. Luminex (either 51/63-plex) was performed from 2008 to 22 2014. Finally, signaling capacity of immune cells was analyzed by phosphorylation 23 cytometry (PhosphoFlow) on mass cytometer in 2013 and flow cytometer in all other years. -
The Rockerverse: Packages and Applications for Containerisation
PREPRINT 1 The Rockerverse: Packages and Applications for Containerisation with R by Daniel Nüst, Dirk Eddelbuettel, Dom Bennett, Robrecht Cannoodt, Dav Clark, Gergely Daróczi, Mark Edmondson, Colin Fay, Ellis Hughes, Lars Kjeldgaard, Sean Lopp, Ben Marwick, Heather Nolis, Jacqueline Nolis, Hong Ooi, Karthik Ram, Noam Ross, Lori Shepherd, Péter Sólymos, Tyson Lee Swetnam, Nitesh Turaga, Charlotte Van Petegem, Jason Williams, Craig Willis, Nan Xiao Abstract The Rocker Project provides widely used Docker images for R across different application scenarios. This article surveys downstream projects that build upon the Rocker Project images and presents the current state of R packages for managing Docker images and controlling containers. These use cases cover diverse topics such as package development, reproducible research, collaborative work, cloud-based data processing, and production deployment of services. The variety of applications demonstrates the power of the Rocker Project specifically and containerisation in general. Across the diverse ways to use containers, we identified common themes: reproducible environments, scalability and efficiency, and portability across clouds. We conclude that the current growth and diversification of use cases is likely to continue its positive impact, but see the need for consolidating the Rockerverse ecosystem of packages, developing common practices for applications, and exploring alternative containerisation software. Introduction The R community continues to grow. This can be seen in the number of new packages on CRAN, which is still on growing exponentially (Hornik et al., 2019), but also in the numbers of conferences, open educational resources, meetups, unconferences, and companies that are adopting R, as exemplified by the useR! conference series1, the global growth of the R and R-Ladies user groups2, or the foundation and impact of the R Consortium3. -
Human Resource Management Strategies for Small- and Medium-Sized Enterprise Project Success Armstrong Matthew Alexis Walden University
Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2018 Human Resource Management Strategies for Small- and Medium-Sized Enterprise Project Success Armstrong Matthew Alexis Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Business Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Management and Technology This is to certify that the doctoral study by Armstrong M. Alexis has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Dorothy Hanson, Committee Chairperson, Doctor of Business Administration Faculty Dr. Teresa Jepma, Committee Member, Doctor of Business Administration Faculty Dr. Matthew Knight, University Reviewer, Doctor of Business Administration Faculty Chief Academic Officer Eric Riedel, Ph.D. Walden University 2018 Abstract Human Resource Management Strategies for Small- and Medium-Sized Enterprise Project Success by Armstrong M. Alexis MBA, Durham University, 2008 MS, University of the West Indies, 1997 BS, University of the West Indies, 1995 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University December 2018 Abstract Critical success factors that contribute to project success in small and medium-sized enterprises (SMEs) have received insufficient attention in research. Guided by the goal- setting conceptual framework, the purpose of this multiple case study was to explore the human resource management (HRM) strategies used by owners of SMEs to achieve project success. -
Download: Casestudy-Researchmethodology
Case Study Design: A Refresher Mansureh Kebritchi, Ph.D. Research Methodology Group Agenda An overview about Major issues related case study to case study Answer your Case study design questions Definition of the Case Study “An empirical inquiry that investigates a contemporary phenomenon (e.g., a “case”) within its real-life context; when the boundaries between phenomenon and context are not clearly evident” (Yin, 2014, p.16) “A case study is an in-depth description and analysis of a bounded system” (Merriam, 2015, p.37). “The “what” is a bounded system (Smith, 1978), a single entity, a unit around which there are boundaries” (Merriam, 2015, p.38)/(Stake, 2005). Definition of the Case Study The most defining characteristics of case study is delimiting the object of the study: the case (Merriam, 2015) • The goal is to understand one thing well: a person, a program, a group, or specific policy; examples: one playground, one band. • Research question must be aligned/define the case/unit of analysis. A noun, seldom a verb, a functioning (Stake, 2006). Real things to visualize. Examples: not training, managing , giving birth but training modules, managers, labor rooms. The “Case” Bounded context The context The Case Examples A study of how older adults learn to use computers. The case/unit of analysis: learners’ experience. Indefinite number of adult leaders can be selected for this study. • Not a case study but a qualitative study One particular program, or classroom of leaners (a bounded system), or one particular learners selected based on success uniqueness, etc. • A case study When to use the Case Study Type of Research Questions relevant to the Case Study • Explanatory/explanatory/descriptive questions • How or why did something happen? Not Appropriate Questions • Cause and effect questions (experimental/quasi- experimental design) • How often something has happened (survey design) When to use the Case Study Data collection in “natural setting” not “derived“ data (Bromley, 1986, p. -
Bruno Colostate 0053A 16562.Pdf (4.546Mb)
DISSERTATION LINKED LIVELIHOODS, LAND-USE, AND IDENTITIES ON TRANSITIONING LANDSCAPES IN NORTHEASTERN COLORADO: A SOCIAL-ECOLOGICAL STUDY Submitted by Jasmine Elizabeth Bruno Department of Forest and Rangeland Stewardship In partial fulfillment of the requirements For the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Spring 2021 Doctoral Committee: Advisor: Maria E. Fernández-Giménez Meena M. Balgopal Paul J. Meiman Robin S. Reid Copyright by Jasmine Elizabeth Bruno 2021 All Rights Reserved ABSTRACT LINKED LIVELIHOODS, LAND-USE, AND IDENTITIES ON TRANSITIONING LANDSCAPES IN NORTHEASTERN COLORADO: A SOCIAL-ECOLOGICAL STUDY Rangeland social-ecological systems in Northeastern (NE) Colorado are undergoing linked land-use, livelihood, and identity transitions. Land change is a spatially and temporally complex process in which land-use decisions cascade through interconnected social and ecological spheres, affecting both humans and the environment. While a wealth of empirical research on land cover changes exists, multiscale, multilevel research on the causes and consequences of linked social- ecological change remains limited. To avoid oversimplification and craft system-appropriate policies in rangeland systems, we require in-depth and process-based knowledge of the causes and consequences of change. Moreover, we must build upon and advance theory to support the role of contextual research in advancing sound practical applications and future inquiry in related systems. Thus, this dissertation applies a theoretically informed multi-method approach to examine the interrelationships among livestock shifting livelihoods, well-being, identities, and associated land change transitions inproducers’ two rangeland-dependent communities in NE Colorado. Social-ecological systems (SESs) theory serves as this dissertation's theoretical foundation, framing rangelands as systems in which humans are embedded within and affect ecosystems and vice versa. -
A History of R (In 15 Minutes… and Mostly in Pictures)
A history of R (in 15 minutes… and mostly in pictures) JULY 23, 2020 Andrew Zief!ler Lunch & Learn Department of Educational Psychology RMCC University of Minnesota LATIS Who am I and Some Caveats Andy Zie!ler • I teach statistics courses in the Department of Educational Psychology • I have been using R since 2005, when I couldn’t put Me (on the EPSY faculty board) SAS on my computer (it didn’t run natively on a Me Mac), and even if I could have gotten it to run, I (everywhere else) couldn’t afford it. Some caveats • Although I was alive during much of the era I will be talking about, I was not working as a statistician at that time (not even as an elementary student for some of it). • My knowledge is second-hand, from other people and sources. Statistical Computing in the 1970s Bell Labs In 1976, scientists from the Statistics Research Group were actively discussing how to design a language for statistical computing that allowed interactive access to routines in their FORTRAN library. John Chambers John Tukey Home to Statistics Research Group Rick Becker Jean Mc Rae Judy Schilling Doug Dunn Introducing…`S` An Interactive Language for Data Analysis and Graphics Chambers sketch of the interface made on May 5, 1976. The GE-635, a 36-bit system that ran at a 0.5MIPS, starting at $2M in 1964 dollars or leasing at $45K/month. ’S’ was introduced to Bell Labs in November, but at the time it did not actually have a name. The Impact of UNIX on ’S' Tom London Ken Thompson and Dennis Ritchie, creators of John Reiser the UNIX operating system at a PDP-11. -
Changes on CRAN 2014-07-01 to 2014-12-31
NEWS AND NOTES 192 Changes on CRAN 2014-07-01 to 2014-12-31 by Kurt Hornik and Achim Zeileis New packages in CRAN task views Bayesian BayesTree. Cluster fclust, funFEM, funHDDC, pgmm, tclust. Distributions FatTailsR, RTDE, STAR, predfinitepop, statmod. Econometrics LinRegInteractive, MSBVAR, nonnest2, phtt. Environmetrics siplab. Finance GCPM, MSBVAR, OptionPricing, financial, fractal, riskSimul. HighPerformanceComputing GUIProfiler, PGICA, aprof. MachineLearning BayesTree, LogicForest, hdi, mlr, randomForestSRC, stabs, vcrpart. MetaAnalysis MAVIS, ecoreg, ipdmeta, metaplus. NumericalMathematics RootsExtremaInflections, Rserve, SimplicialCubature, fastGHQuad, optR. OfficialStatistics CoImp, RecordLinkage, rworldmap, tmap, vardpoor. Optimization RCEIM, blowtorch, globalOptTests, irace, isotone, lbfgs. Phylogenetics BAMMtools, BoSSA, DiscML, HyPhy, MPSEM, OutbreakTools, PBD, PCPS, PHYLOGR, RADami, RNeXML, Reol, Rphylip, adhoc, betapart, dendextend, ex- pands, expoTree, jaatha, kdetrees, mvMORPH, outbreaker, pastis, pegas, phyloTop, phyloland, rdryad, rphast, strap, surface, taxize. Psychometrics IRTShiny, PP, WrightMap, mirtCAT, pairwise. ReproducibleResearch NMOF. Robust TEEReg, WRS2, robeth, robustDA, robustgam, robustloggamma, robustreg, ror, rorutadis. Spatial PReMiuM. SpatioTemporal BayesianAnimalTracker, TrackReconstruction, fishmove, mkde, wildlifeDI. Survival DStree, ICsurv, IDPSurvival, MIICD, MST, MicSim, PHeval, PReMiuM, aft- gee, bshazard, bujar, coxinterval, gamboostMSM, imputeYn, invGauss, lsmeans, multipleNCC, paf, penMSM, spBayesSurv, -
A Tool for Researching Chronic Pelvic Pain Using Thematic Analysis
QUALITATIVE RESEARCH: PRACTICES AND CHALLENGES USING RQDA IN QUALITATIVE DATA ANALYSIS: A TOOL FOR RESEARCHING CHRONIC PELVIC PAIN USING THEMATIC ANALYSIS Bruna Helena Mellado1, Catarina Brandão2, 3 , Taynara Louisi Pilger1 , Francisco José Candido dos Reis1 1Department of Gynecology and Obstetrics, Ribeirão Preto Medical School, University of São Paulo, Brazil. [email protected] [email protected]; [email protected] 2Faculty of Psychology and Educational Sciences of the University of Porto, Portugal. [email protected] 3 Psychology Center of the University of Porto, Portugal Abstract. Computer-assisted qualitative data analysis software (CAQDAS) provides tools that help researchers develop qualitative research projects. These software packages support users with tasks such as transcription analysis, text encoding and interpretation, writing and annotation, searching, recursive abstraction, and data mapping, enabling the use of different methods (e.g., grounded theory) and analysis techniques (e.g., content analysis or discourse analysis). The choice of CAQDAS is directly related to the researcher’s chosen methodological approach. The amount and variety of software available often makes the choice process difficult. In Brazil, the data on the use of CAQDAS is still scarce. Commercial software packages are more frequently cited. Open- source packages, like RQDA, are less popular. In this chapter, we present our experience with the use of RQDA to analyze the data from a qualitative study on chronic pelvic pain in women. Keywords: Computer-Assisted Qualitative Data Analysis Software, RQDA, Thematic Analysis, Pelvic Pain. 1. INTRODUCTION The field of qualitative research is characterized by different epistemological perspectives and methodological orientations, which often leads to intense academic debate (Ghedin & Franco, 2008; Merriam, 2007). -
R: a Swiss Army Knife for Market Research
R: A Swiss Army Knife for Market Research Enhancing work practices with R Martin Chan – Consultant, Rainmakers CSI 12th September, 2018 1 2 This presentation is about using R in business environments or conditions where its usage is less intuitively suitable… … and a story of how R has been transformative for our work practices 2 3 Who are we? What do we do? 3 4 What How Where Answer strategic Estimate size of market, and size of Across multiple questions to help our opportunity, anticipating trends industries and clients grow profitably markets Utilise resources available within an Inform strategic decisions organisation (e.g. stakeholder knowledge, • FMCG through creative and existing research) • Finance & analytical thinking Insurance Develop consumer targeting frameworks – • Travel identify core consumers and areas of • Media opportunities 4 5 A team with a mix of backgrounds from strategy, brand planning, marketing, research… (where analytics is a key, but only one of the components of our work) 5 6 What’s different about the use of R in our work? 6 Challenges of Using R Nature of data: Nature of U&A Client 1 2 3 disparate, patchy data requirement and expectations (of outputs) U&A – research with the aim to understand a market and identify growth opportunities by answering questions on whom to target, with what, and how. (Source: https://www.ipsos.com/en/ipsos-encyclopedia- 7 usage-attitude-surveys-ua) Nature of data: 1 disparate, patchy 8 9 Historical survey data – often designed for different purposes Stakeholder Interviews Our data come (Qualitative) together in and collected from different samples different forms, like pieces of Population / Demographic data (from census, World Bank Customer Interviews (Qualitative) JIGSAW research etc.) Pricing data Historical segmentation work (e.g. -
Investigating Computer Assisted Qualitative Data Analysis Software (CAQDAS)
1 Proposal for Workshop for iConference 2019 Workshop Title: InVivo Inspiration: Investigating Computer Assisted Qualitative Data Analysis Software (CAQDAS) Organizers: Marie L. Radford1, Vanessa Kitzie2, Diana Floegel3, Lynn Silipigni Connaway4, Jenny Bossaller5, Sean Burns6 Abstract: This half-day workshop will provide an overview and comparison of computer- assisted qualitative data analysis software (CAQDAS). Since adoption of these programs requires substantial time commitment and/or budget expenditure, it is vital to understand their capabilities and limitations, as well as the types of data best suited for each platform. A panel of experts will present advantages and disadvantages of several software packages, then demonstrate how to use popular CAQDAS platforms, including commercial (i.e., NVivo, ATLAS.ti, Qualtrics, Dedoose) and open source (i.e., RQDA) programs. Panelists will then invite attendees to participate in interactive breakout tables to learn more about and experiment with a product of their choice. Panelists will answer attendees’ questions and demonstrate advanced features. The workshop will conclude with a general Q&A session. Both novice and experienced researchers will benefit by learning about the variety of available CAQDAS options. Description: Purpose and Intended Audience Are you a novice or experienced researcher drowning in qualitative data? Are you wondering how on earth you will ever have the time to analyze reams of text, audio files, video footage, and field notes? Would you like to learn about opportunities and pitfalls involved in switching to a digital analysis tool? If so, this is the workshop for you. In an interactive and engaging workshop, experts in qualitative data analysis will introduce CAQDAS and will present important considerations for those wondering whether or not to adopt this type of software.