- 101
- 43 361
useR! Conference
Приєднався 12 кві 2022
useR! Conference is an all-virtual conference. useR! is an annual nonprofit conference organized by R community volunteers and supported by the R Foundation. Attendees include R developers and users who are data scientists, business intelligence specialists, analysts, statisticians from academia and industry, and students. The conferences showcase applications of R software and developments in the software itself, as well as new and updated R packages that provide boundless additional functionality to R. Community contributions form the foundation of useR! conferences.
Fifteen Years of the R Journal - Mark van der Loo
The first issue of the R Journal was published in June 2009. Run by volunteers from academia, government and industry, the journal has grown into an increasingly popular outlet for scientific research on anything related to R. At the time of writing the Journal has an impact factor of 1.673. In this talk I will look back at the origins and history of The R Journal. I will look back on the people involved and the formal organisation of the journal, including associate editors, editors, and the advisory board. We will take a detailed look at the current editorial process and production of issues in HTML and pdf format will be explained. This will yield extensive tips and tricks that help aspiring authors to get their submissions processed quickly. Finally, we will look into the future developments of the R Journal.
Mark van der Loo, Statistics Netherlands
Mark is a Senior Researcher at Statistics Netherlands and a Research Fellow at the Leiden Institute for Advanced Computer Science at the University of Leiden. Mark published his first package in 2009 and has since co-authored about 20 R packages, a book on statistical data cleaning with R (Wiley, 2018) and peer reviewed papers in the area of Statistical Computing. Mark has been involved with The R Journal since 2021 and is currently its Editor-in-Chief.
Mark van der Loo, Statistics Netherlands
Mark is a Senior Researcher at Statistics Netherlands and a Research Fellow at the Leiden Institute for Advanced Computer Science at the University of Leiden. Mark published his first package in 2009 and has since co-authored about 20 R packages, a book on statistical data cleaning with R (Wiley, 2018) and peer reviewed papers in the area of Statistical Computing. Mark has been involved with The R Journal since 2021 and is currently its Editor-in-Chief.
Переглядів: 87
Відео
Translate R for Global Reach - Binod Jung Bogati
Переглядів 212 місяці тому
Do you use R and want to help extend its global reach? Our talk on translating R is just for you! Translation involves translating R's messages, warnings, and errors from English into other languages, making it accessible to a global audience. Support for translation has been part of R since 2005, but it relies heavily on community contributions to provide the necessary translations and help ke...
The Retirement of R Packages with Many Reverse Dependencies - Edzer Pebesma & Roger Bivand
Переглядів 602 місяці тому
Full title: R Evolution: The Retirement of R Packages with Many Reverse Dependencies - Edzer Pebesma & Roger Bivand We report on a project where three older R packages for spatial analysis: rgdal for reading and writing vector and raster data and coordinate transfromation, rgeos for geometric transformations and predicates and maptools have been taken off CRAN on Oct 16, 2023 because their main...
Using R to Co-Create an Inclusive Data Analysis Approach [..] - Lois Adler-Johnson
Переглядів 652 місяці тому
Full title: Using R to Co-Create an Inclusive Data Analysis Approach with the HBCU Health Equity Data Consortium - Lois Adler-Johnson From February 2023 to February 2024, the Historically Black Colleges and Universities (HBCU) Health Equity Data Consortium (HEDC) in North Carolina (NC) deployed the COVID-19 Impact Survey to address critical data gaps on the pandemic’s impact on households acros...
Mastering Plumber Structure: Your API's Solutions. - Adam Forys & Magdalena Krochmal
Переглядів 702 місяці тому
This presentation offers a comprehensive analysis of the structural design patterns within the Plumber API framework. We will explore a spectrum of approaches, ranging from fundamental implementations to sophisticated techniques such as 'Plumber as code' and 'Plumber as package.' Each structure will be examined for its advantages and best-use scenarios. Finally, we will provide guidance on sele...
What They Forgot to Teach You About Shiny Development in Production - Mohamed El Fodil Ihaddaden
Переглядів 2332 місяці тому
The amount of documentation about Shiny is getting larger and larger. The official Shiny website offers a nice interface with live examples. Many books and video tutorials have been published about the subject. However, the amount of documentation and freely available knowledge about Shiny development in a production context remains scarce. As such, many Shiny developers, even the experienced o...
Getting the Most Out of Test-Driven Development for Shiny - Jakub Sobolewski
Переглядів 832 місяці тому
Tests are not only a way of catching bugs but also a way of building software. During the talk, I’ll share how we can use Test-Driven Development to build Shiny apps. We’ll start with tips on gathering requirements in a format that is easy to translate to test cases. Implementing requirements as automated tests helps us get confidence we’ve built the correct code. This is crucial when using Shi...
Tidymodels: Now Also for Time-to-Event Data! - Hannah Frick
Переглядів 1022 місяці тому
The tidymodels framework is a collection of packages for modeling and machine learning using tidyverse principles. In addition to regression and classification, it now also supports censored regression for time-to-event data. This type of data with potential censoring requires dedicated models and performance metrics from the field of survival analysis. While the censored package has made survi...
Dynamic Prediction with Numerous Longitudinal Covariates - Mirko Signorelli
Переглядів 1282 місяці тому
To make informed decisions, clinicians and patients rely on accurate predictions of the probability to experience adverse events such as dementia, cancer or death. Dynamic prediction models can update the probability of experiencing an event as more longitudinal data is collected. However, traditional joint modelling is computationally unfeasible with more than a handful of longitudinal covaria...
Forecast Reconciliation Made Easy: The FoReco Package - Daniele Girolimetto
Переглядів 552 місяці тому
Forecast reconciliation is a post-forecasting approach to ensure the coherence of forecasts across constraints (not just simple aggregation). It harmonizes individual predictions to meet predefined relationships, leading to a consistent and comprehensive picture. This can include ensuring market share forecasts for different brands sum up to the total, or guaranteeing some property (e.g. non ne...
[Keynote] Keep R weird - Kelly Bodwin
Переглядів 1,5 тис.4 місяці тому
What is it about R that inspires such love, devotion, and creativity in us? This talk is an affectionate journey through the many things that make R and her community gloriously weird. We’ll dip our toes into the history of programming to learn more about the unusual structures and aspects of the R language that send computer scientists spinning: dynamic environments, first-class functions, S3 ...
[Keynote] Some things you can’t read from a NEWS file - Torsten Hothorn
Переглядів 3205 місяців тому
Some things you can’t read from a NEWS file Torsten Hothorn, University of Zürich Longterm package maintenance comes with its own challenges and benefits. While NEWS files document technical histories of packages, the non-technical, methodological and social aspects of package development are rarely discussed in a wider audience. Based on personal experience, this keynote presentation will shed...
[Keynote] How Your Code Might Get Rusty, And What You Can Do About This - Maëlle Salmon
Переглядів 7695 місяців тому
useR! 2024 Keynote: How Your Code Might Get Rusty, And What You Can Do About This Maëlle Salmon, Cynkra & rOpenSci Do you ever find yourself working on a codebase that has gotten a bit rusty over time? Or read an old script and have trouble understanding what it does? It happens to me regularly, be it code that I wrote myself, or code I was tasked with, such as the established igraph R package....
Contributing Translations to R - Gergely Daroczi
Переглядів 1606 місяців тому
The R Project has a global and active community with members speaking different languages around the world, often with the need or preference to be able to use R a language instead of English. To support this, R Core has implemented GNU gettext helpers enabling the translation of messages, warnings, errors etc since R version 2.1.0 (April 2005). This tutorial will provide a short overview of th...
Automating Updates to Shiny Dashboards Deployed on Shinyserver - Clinton David
Переглядів 1436 місяців тому
I presume that, as R developers, we’ve heard of or perhaps used shiny package to develop web applications, and that, we can attest to the fact that it has emerged as a popular framework for developing dashboards in R. These shiny dashboards provide a dynamic platform for data exploration, analysis, and dissemination, making them invaluable tools for researchers, analysts, and decision-makers. H...
Deploy and Monitor ML Pipelines with Open Source and Free Applications - Rami Krispin
Переглядів 4286 місяців тому
Deploy and Monitor ML Pipelines with Open Source and Free Applications - Rami Krispin
Missing Data Exploration, Imputation, and Evaluation - Hanne Oberman
Переглядів 3986 місяців тому
Missing Data Exploration, Imputation, and Evaluation - Hanne Oberman
Flexible Additive Models for Survival and Event-History Analysis - Andreas Bender & Johannes Piller
Переглядів 1626 місяців тому
Flexible Additive Models for Survival and Event-History Analysis - Andreas Bender & Johannes Piller
Causal Inference in R: The Whole Game - Malcolm Barrett
Переглядів 1,1 тис.6 місяців тому
Causal Inference in R: The Whole Game - Malcolm Barrett
Oops All Solvers: Democratizing Access to Water Treatment Models Using R - Sierra Johnson
Переглядів 1096 місяців тому
Oops All Solvers: Democratizing Access to Water Treatment Models Using R - Sierra Johnson
R Consortium's R-based Test Submission Package for FDA Evaluation - Joel Laxamana
Переглядів 3366 місяців тому
R Consortium's R-based Test Submission Package for FDA Evaluation - Joel Laxamana
Health Economic Assessment Tool for Walking and Cycling (HeatR): Thomas Gotschi & Tomasz Szreniawski
Переглядів 946 місяців тому
Health Economic Assessment Tool for Walking and Cycling (HeatR): Thomas Gotschi & Tomasz Szreniawski
Leveraging R-Ladies Paris Reach for Community Impact - Chaima Boughanmi
Переглядів 1106 місяців тому
Leveraging R-Ladies Paris Reach for Community Impact - Chaima Boughanmi
Community Detection for Extremely Large Networks - Aidan Lakshman
Переглядів 936 місяців тому
Community Detection for Extremely Large Networks - Aidan Lakshman
Transforming Data Into Information: Overcoming Challenges in Educational Data Analysis - N. da Silva
Переглядів 2226 місяців тому
Transforming Data Into Information: Overcoming Challenges in Educational Data Analysis - N. da Silva
Detecting Abnormal Fish Behaviors with Machine Learning - Enrique Garcia-Ceja
Переглядів 1196 місяців тому
Detecting Abnormal Fish Behaviors with Machine Learning - Enrique Garcia-Ceja
Learning Together at the Data Science Learning Community - Jon Harmon
Переглядів 1826 місяців тому
Learning Together at the Data Science Learning Community - Jon Harmon
Data pipeline to analyse FODESAF's cash flow: key outputs in R Quarto - Roberto Delgado Castro
Переглядів 886 місяців тому
Data pipeline to analyse FODESAF's cash flow: key outputs in R Quarto - Roberto Delgado Castro
Stop Making Spaghetti (Code) - Nicola Rennie
Переглядів 1,8 тис.6 місяців тому
Stop Making Spaghetti (Code) - Nicola Rennie
Unlock Your Data Insights Faster: The 'CohortBuilder' Way. - Adam Forys & Krystian Igras
Переглядів 2106 місяців тому
Unlock Your Data Insights Faster: The 'CohortBuilder' Way. - Adam Forys & Krystian Igras
Great insights into this method. I have one question: when it comes to having factors as predictors, is it best to leave them as they are (for example 1 or 0 if a treatment is in place or not) or should they be one=hot encoded?
Sa7a walid bladi cherftna
Sa7a walid bladi cherftna
Hi Joel! Thank you for the excellent presentation. I tried setting up my R environment and following instructions step by step; however, I faced an error and needed help finding the solution online. Therefore, posting here hoping you could point to a solution. Thank you in advance. The error goes as: "Error in `haven::read_xpt()`: ! This kind of input is not handled."
Bayu budi utomo
Great presentation
Awesome work. Thanks.
9:42
Super entertaining and informative! Thanks!
Awesome presentation.
If just there was not so much reverberation on the right channel. People, if you can, listen to the left ear channel. That is the one with suitable audio quality.
@@HarmonicaTool I thought the audio was good. I didn’t try it in mono. If it’s that bad, you can always re-encode the video in mono and problem solved. I can assist if you like.
@RobertR1611 Oh, I listened through earphones and then it is disturbing. And no, I am not going to copy somebodies video to do my audio editing on their work. Thank you for offering the help but that is for the channel to decide.
Very important message presented brilliantly 🎉
Thank you, Joel!
Unfortunately very poor audio quality. Over the whole video, hard to stand.
Thanx for the video...help me a lot
Thank you for the great presentation and explanation!
🦀 rusty
Great presentation
Cool to see Nix stuff in Lux :)
Amazing thanks for the presentation
Great. Do you share the code for the revealjs?
Really great talk! And thank you for mentioning my book :)
Also very curious about his comments on LLMs. He's right. An LLM is not creative. And will probably never replace humans at the high level stuff.
Thanks for this quote, can you help advise which part in this video Hadley said that? Around which timepoint
@@pengzhang1263 LLM discussion starts at 21:50.
Very interested in nanoparquet. I had the same complaint about arrow. Big package with a lot of functionality and a lot of dependencies. Would appreciate a lightweight package to read and write parquet files!
One of the most productive people in the world! He's even debugging during the interview!
This was such a great interview. Thanks for conducting this, Audrey! I always like to hear from primary sources. And here you have two of the founding members of the R community. They have such insightful comments!
Thank you so much for the introduction and for open code!
Emil, thank you, I don´t know if you would read this... but maybe someone could answer. I have a theoretical doubt, wouldn't it be better to convert to factor after having the factor type predictor variables separated in the split? that way the levels that the variable in train knows would not be informed by the levels that test knows they could take.
Thank you very much🎉
Thanks for the tutorial I am using adehabitatHR, sp and other related spatial package to calculate Home range of individual species through adehabitatHR I am able to generate the MCP and Kernel density home range of individuals. But the output of area calculation is very low e-9 I used the UTM projection for zone 45N please help me.. Even when I change the projection to WGS84 the area remains the same Can you tell me what is wrong
🎉🎉🎉🎉🎉
gracias por este video, me queda bien claro el uso de ggplot. con muchos detalles
Thanks for this! Very useful.
Podrían compartir por favor el material del taller
interested in how is this compared to a naive regression based approach?
Super video
(MRAN) website and CRAN Time Machine will be retired on July 1, 2023.
amazing tutorial - thank you all - Rahul and Ramin in particular
we want to know from the beginning . it start after some video parts passed away
it's very useful for beginners. Thanks, Rahul, so nice hands-on tutorial
Thanks for uploading this -- very useful content.
Please attache dataset here also.
Newer versions of the slides/handouts are at hbiostat.org/rmsc
Session starts at 13:20
Thank you.
Its very useful presentation. Thanks alot. I am looking for the heterogenous treatment effect using DML. Please let me know if you have any resources for heterogenous treatment effect estimation.
Most excellent!!
Thank you for the walk through!
1:30 Knowledge catalogs with TKCat 19:55 Linked dataframes 39:17 DuckDB All In-Process Analytical DBMS ("The SQLite for Analytics", short demo at 50:40) 58:50 Database list against the matrix: use of tax list an vegtable for the assessment of vegetable-plot data
Too much environmental.... too little ecology 🙁
thanks for yr wonderful lecture , do u mind providing the slide link?
yes, sure! You'll find all materials here: docs.doubleml.org/tutorial/stable/2022/06/18/welcome-user-2022/
Presentation begins at 10:21.
Is there a transcript available, somewhere? People really shouldn’t have to rely on craptions, especially for talks about accessibility… Thanks.