#rstats — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #rstats, aggregated by home.social.
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New from the R Consortium nlmixr2 Working Group:
The nlmixr2 Working Group is expanding what open-source R tooling can support in pharmacometrics, including time-to-event modeling workflows that are important in clinical and drug-development settings.
This new post highlights technical work from Justin Wilkins and the nlmixr2 Development Team on fitting parametric time-to-event models in nlmixr2.
Read more:
https://r-consortium.org/posts/survival-analysis-with-nlmixr2/#RStats #Pharmacometrics #PKPD #ClinicalResearch #OpenSource
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Updating the graphical materials for the new edition of the monograph on the thermodynamic modeling of processes in technogenic waters. The figures present pe-pH stability (Pourbaix) diagrams for the vanadium and zinc systems, calculated using the PHREEQC core engine. Unlike simplified "water–element" systems, these models compute the thermodynamic equilibrium of the comprehensive solution matrix, accounting for actual macrocomponent concentrations, ionic strength, and ligand competition at every point of the computational space. Utilizing multicomponent calculations allows for the analysis of physicochemical processes in real water samples, rather than simply reproducing idealized "textbook diagrams".
#Geochemistry #PHREEQC #RStats #MineWater #EnvironmentalScience #DataScience #SvystunovaGully #RedModRphree #FOSS
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tools::file_path_sans_ext(crap.R)
is better than my homemade regex (even if it is a regex inside)
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I like understanding how ideas for charts come about and it’s interesting to read @[email protected]’s explainer on that local election chart I saw everywhere. #rstats #dataviz
What happens when a chart goes... -
#RStats #bytebeat - minimalist audio generation
# Search for "bytebeats'
`%>>%` <- bitwShiftR
`%&%` <- bitwAnd
`%|%` <- bitwOrt <- seq(0, 8000 * 4)
snd <- (t * (((t %>>% 12) %|% (t %>>% 8)) %&% (63 %&% (t %>>% 4))) )
audio::play(snd %% 255, rate = 8000)
Sys.sleep(4)snd <- t * (42 %&% (t %>>% 10))
audio::play(snd %% 255, rate = 8000) -
Tidy Modeling with R: https://www.tmwr.org/ #rstats #machinelearning #datascience
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Tidy Modeling with R: https://www.tmwr.org/ #rstats #machinelearning #datascience
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Tidy Modeling with R: https://www.tmwr.org/ #rstats #machinelearning #datascience
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Tidy Modeling with R: https://www.tmwr.org/ #rstats #machinelearning #datascience
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Tidy Modeling with R: https://www.tmwr.org/ #rstats #machinelearning #datascience
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May news 🗞️ #RStats
🎉 15 Years of rOpenSci, and we’re just getting started
✍️ Champions Program update
🙌 May is Maintainer Month
📬 Software-Review update
🚀 Social media cards for R-universe
📆 Coworking
🗒️ Blog posts
🧰 Package development corner
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May news 🗞️ #RStats
🎉 15 Years of rOpenSci, and we’re just getting started
✍️ Champions Program update
🙌 May is Maintainer Month
📬 Software-Review update
🚀 Social media cards for R-universe
📆 Coworking
🗒️ Blog posts
🧰 Package development corner
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May news 🗞️ #RStats
🎉 15 Years of rOpenSci, and we’re just getting started
✍️ Champions Program update
🙌 May is Maintainer Month
📬 Software-Review update
🚀 Social media cards for R-universe
📆 Coworking
🗒️ Blog posts
🧰 Package development corner
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May news 🗞️ #RStats
🎉 15 Years of rOpenSci, and we’re just getting started
✍️ Champions Program update
🙌 May is Maintainer Month
📬 Software-Review update
🚀 Social media cards for R-universe
📆 Coworking
🗒️ Blog posts
🧰 Package development corner
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May news 🗞️ #RStats
🎉 15 Years of rOpenSci, and we’re just getting started
✍️ Champions Program update
🙌 May is Maintainer Month
📬 Software-Review update
🚀 Social media cards for R-universe
📆 Coworking
🗒️ Blog posts
🧰 Package development corner
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Imagine you’re evaluating a new cancer treatment. It reduces tumor size in most patients, but some experience severe side effects. Would we consider the new treatment better?
Read more about it in a new post on superiority in the multivariate context.
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Heads up for those using Remote SSH with positron/vscode: the .positron-server folder can get real big real fast. Today I notices that the folder was more than 300.000 files big, so I nuked it from orbit.
I believe the issue is that positron doesn't remove old versions, and the server itself is 1gb and around 20.000 files. -
Heads up for those using Remote SSH with positron/vscode: the .positron-server folder can get real big real fast. Today I notices that the folder was more than 300.000 files big, so I nuked it from orbit.
I believe the issue is that positron doesn't remove old versions, and the server itself is 1gb and around 20.000 files. -
Heads up for those using Remote SSH with positron/vscode: the .positron-server folder can get real big real fast. Today I notices that the folder was more than 300.000 files big, so I nuked it from orbit.
I believe the issue is that positron doesn't remove old versions, and the server itself is 1gb and around 20.000 files. -
Heads up for those using Remote SSH with positron/vscode: the .positron-server folder can get real big real fast. Today I notices that the folder was more than 300.000 files big, so I nuked it from orbit.
I believe the issue is that positron doesn't remove old versions, and the server itself is 1gb and around 20.000 files. -
Heads up for those using Remote SSH with positron/vscode: the .positron-server folder can get real big real fast. Today I notices that the folder was more than 300.000 files big, so I nuked it from orbit.
I believe the issue is that positron doesn't remove old versions, and the server itself is 1gb and around 20.000 files. -
🦀 smoothbp has been submitted to CRAN!
Hierarchical piecewise regression with smoothed change-points in #RStats — multi-breakpoint models, spike-and-slab regularisation for automatic breakpoint selection, and a fast MCMC sampler written in Rust under the hood.
Dev version: github.com/ABindoff/smoothbp
#rstats #statistics #bayesian -
🦀 smoothbp has been submitted to CRAN!
Hierarchical piecewise regression with smoothed change-points in #RStats — multi-breakpoint models, spike-and-slab regularisation for automatic breakpoint selection, and a fast MCMC sampler written in Rust under the hood.
Dev version: github.com/ABindoff/smoothbp
#rstats #statistics #bayesian -
As art: wonderful. As illustration: wonderful. As a tool for data communication: avoid. #rstats
RE: https://bsky.app/profile/did:plc:guty4nrzefv72m7sndu3vrfu/post/3mmtq2yq7tc25 -
Let a fancy genetic algorithm run for 13+ hours only for it to return less good results than my naive algorithm. :blobcatmaths:
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Let a fancy genetic algorithm run for 13+ hours only for it to return less good results than my naive algorithm. :blobcatmaths:
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Let a fancy genetic algorithm run for 13+ hours only for it to return less good results than my naive algorithm. :blobcatmaths:
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Let a fancy genetic algorithm run for 13+ hours only for it to return less good results than my naive algorithm. :blobcatmaths:
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Need to a convenient way to load @[email protected] 's #Rstats tools? Use the epiverse, a collection of R packages we maintain to facilitate data analysis
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Need to a convenient way to load @[email protected] 's #Rstats tools? Use the epiverse, a collection of R packages we maintain to facilitate data analysis
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Cheers to my student who wrote on their final exam code screenshot for an #Rstats course:
dfAB <- length(variableA)-2
# (It's 5-2 which is 3 but why use brain when R do trick) -
Cheers to my student who wrote on their final exam code screenshot for an #Rstats course:
dfAB <- length(variableA)-2
# (It's 5-2 which is 3 but why use brain when R do trick) -
Cheers to my student who wrote on their final exam code screenshot for an #Rstats course:
dfAB <- length(variableA)-2
# (It's 5-2 which is 3 but why use brain when R do trick) -
Cheers to my student who wrote on their final exam code screenshot for an #Rstats course:
dfAB <- length(variableA)-2
# (It's 5-2 which is 3 but why use brain when R do trick) -
Cheers to my student who wrote on their final exam code screenshot for an #Rstats course:
dfAB <- length(variableA)-2
# (It's 5-2 which is 3 but why use brain when R do trick) -
Extract tables from pdfs with {tabulapdf} https://docs.ropensci.org/tabulapdf/ #rstats #datasciece
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Extract tables from pdfs with {tabulapdf} https://docs.ropensci.org/tabulapdf/ #rstats #datasciece
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Extract tables from pdfs with {tabulapdf} https://docs.ropensci.org/tabulapdf/ #rstats #datasciece
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Extract tables from pdfs with {tabulapdf} https://docs.ropensci.org/tabulapdf/ #rstats #datasciece
