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CRAN . R-PROJECT . ORG {}

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Cran.r-project.org Make Money
  6. Keywords
  7. Topics
  8. External Links
  9. Libraries

We are analyzing https://cran.r-project.org/web/packages/loo/index.html.

Title:
CRAN: Package loo
Description:
Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo, as described in Vehtari, Gelman, and Gabry (2017) &lt;<a href="https://doi.org/10.1007%2Fs11222-016-9696-4" target="_top">doi:10.1007/s11222-016-9696-4</a>&gt;. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.
Website Age:
25 years and 8 months (reg. 1999-10-27).

Matching Content Categories {📚}

  • Insurance
  • Shopping
  • Fitness & Wellness

Content Management System {📝}

What CMS is cran.r-project.org built with?

Custom-built

No common CMS systems were detected on Cran.r-project.org, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of cran.r-project.org audience?

💥 Very Strong Traffic: 200k - 500k visitors per month


Based on our best estimate, this website will receive around 250,019 visitors per month in the current month.
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How Does Cran.r-project.org Make Money? {💸}

We don’t know how the website earns money.

Some websites aren't about earning revenue; they're built to connect communities or raise awareness. There are numerous motivations behind creating websites. This might be one of them. Cran.r-project.org has a revenue plan, but it's either invisible or we haven't found it.

Keywords {🔍}

loo, crossvalidation, bayesian, aut, leaveoneout, models, package, ctb, lootgz, reverse, approximate, gabry, errors, predictive, loozip, rrelease, roldrel, efficient, vehtari, gelman, importance, weights, stacking, model, depends, imports, suggests, bayesplot, brms, rstan, rstanarm, jonah, citation, stan, programs, binaries, arm, waic, fit, markov, chain, monte, carlo, dois, approximation, pareto, smoothed, sampling, psis, procedure,

Topics {✒️}

/stan-dev/loo/issues license paul-christian bürkner [aut] k-fold cross-validation bayesian models fit regularizing importance weights model weighting techniques ben goodrich [ctb] juho piironen [ctb] bruno nicenboim [ctb] bayesian cran checks estimated predictive errors gz windows binaries måns magnusson [aut] yuling yao [aut] topi paananen [aut] moment matching leave loo results documentation pandoc-citeproc citation walker reverse suggests jonah gabry [cre tridimregression reverse imports aki vehtari [aut] andrew gelman [aut] zip macos binaries canonical form https stan programs org/package=loo efficient leave predictive errors //mc-stan mc-stan org/loo/ loo author loo package stats suggests reverse depends cross-validation org needscompilation holdout validation models reference manual pdf vignettes package source r-devel r-release r-oldrel websdm linking r-project aut] leave

External Links {🔗}(8)

Libraries {📚}

  • Moment.js

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