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Prikvačeni tweet
Pleased to announce that
#tidybayes v2.0 (SLABS FOR DAYS edition) hit CRAN today.#rstats Lots of new stuff in this version: A THREADPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Matthew Kay proslijedio/la je Tweet
Love this story featuring tips from
@JessicaHullman &@SteveFranconeri on better visualizing uncertainty. One of their tips: instead of a bar chart, use an icon array or a “risk theater”pic.twitter.com/6ivGtnH5Bk
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Matthew Kay proslijedio/la je Tweet
I am so very excited to announce that {ggeasy} is now a CRAN package! Having trouble remembering how to tweak your {ggplot2} components? We got you covered. https://CRAN.R-project.org/package=ggeasy pic.twitter.com/iCdlgrY8or
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Matthew Kay proslijedio/la je Tweet
Could some phoneticians who use R try out my readtextgrid package on their textgrids? It does only one thing (reads textgrids into dataframes). I've been using it for months, but testing from other languages/settings would help.https://github.com/tjmahr/readtextgrid …
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Matthew Kay proslijedio/la je Tweet
i'm just going to fix this one little bug. oh first, i should set up a test case. oh wait, now something is wrong in docs. ah a dependency deprecated a function. ah ah ahpic.twitter.com/Wwy32F2idr
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Anyhue, read more about it in the changelog: http://mjskay.github.io/tidybayes/news/index.html#tidybayes-200 … Thanks to everyone who's given feedback on the package, and of course to the great software it builds upon, like
@mcmc_stan,#brms,#rstanarm,#ggplot, the#tidyverse, etc.Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Finally and more esoterically, tidybayes now includes the marginal distribution for a single cell in an LKJ-distributed correlation matrix, to help with visualizing LKJ priors (because what even does an LKJ prior imply??) http://mjskay.github.io/tidybayes/reference/lkjcorr_marginal.html …pic.twitter.com/DF4bRaV4kP
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For more on these new geoms, check out the new slabinterval vignette:http://mjskay.github.io/tidybayes/articles/slabinterval.html …
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It's also easier to create Kruschke-style distribution-of-distribution plots for posterior predictions using the new stat_dist_slabh() applied to draws from the joint posterior for mu and sigma.pic.twitter.com/nF0NHBmlvr
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That means you can now do halfeyes, gradient plots, lineribbons, dotplots, and everything else ON FREQUENTIST MODELS with broom + tidybayes by mapping estimates, standard errors, and (optionally) degrees of freedom onto distribution params. E.g. here's halfeyes and lineribbonspic.twitter.com/XlWe27Cuog
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The ability to visualize analytical distirbutions easily also makes it easy to do *frequentist* visualization in tidybayes (blasphemy!!!). See this vignette:http://mjskay.github.io/tidybayes/articles/freq-uncertainty-vis.html …
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...or this visualization of priors from a
#brms model, also enabled by the new parse_dist() function which turns prior specs like "normal(0,1)" into columns that can be mapped onto aesthetics in a ggplot.pic.twitter.com/Lw7m9stxAe
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The "stat_dist_..." subfamily also allows visualization of analytical distributions using all the same geoms above. E.g. This visualization showing a Beta(alpha, 10) distribution for different values of alpha...pic.twitter.com/tKHg3gzRKy
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Variables can be mapped onto fill and color within-slabs, which both enables gradient plots (above) and allows custom plots, like this plot of a region of practical equivalence (ROPE)pic.twitter.com/FZh5Bo0dZ1
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While a variety of "template" geoms and stats are provided for common combinations, numerous custom combinations are possible. E.g. we can remap the CCDF function onto alpha instead of slab thickness to make a CCDF gradient plot.pic.twitter.com/vLLgms0tt5
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The dotplots, btw, automatically choose bin size based on the viewport.pic.twitter.com/4DberPeTcm
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...and quantile dotplots, amongst other things. (dodge-able, just like everything else :) )pic.twitter.com/D1dL7h7yoy
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...CCDF barplots... (also note dodging is supported by all slab+interval geoms)pic.twitter.com/VCM8vGapF3
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But also enables a variety of new geoms, like histogram+intervals...pic.twitter.com/urxFscgJls
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The slab+interval meta-geom now drives old standards like eyes and half-eyes...pic.twitter.com/MNtuMTyDBt
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