Create accountLogin

Recent searches

No recent searches

Search options

Only available when logged in.
urbanists.social is one of the many independent Mastodon servers you can use to participate in the fediverse.
We're a server for people who like bikes, transit, and walkable cities. Let's get to know each other!

Administered by:

Server stats:

523
active users

urbanists.social: AboutProfiles directoryPrivacy policy

Mastodon: AboutGet the appKeyboard shortcutsView source codev4.3.8

#package

1 post1 participant0 posts today
Public
Eric Maugendre

The European Commission released its "AI Continent Action Plan" last week. This high-level communication lays down the various initiatives the European Commission is pursuing to support Europe's AI ambitions and AI uptake: iapp.org/news/a/a-view-from-br

IAPP · A view from Brussels: What is and isn't in the EU's AI Continent Action PlanBy Isabelle Roccia
#deregulation#DataCenters#Cloud
Replied in thread
Public
Felix Palmen :freebsd: :c64:

@peppe Actually, (almost) every #FreeBSD #port should also be available as a binary #package. When one is missing, this typically indicates a build failure on the latest bulk run. Trying to build it yourself won't help here unless there was a fix committed to the ports tree meanwhile, in which case the package will also "reappear" within few days.

Public
fraud

I'm trying to make a _good_ .deb package.

Yet I'm having a hard time finding a blog post where someone explain their experience going from bare minimum to a fairly advanced package with multiple stuff going pre and post install.

By _good_ I also mean something that helps understanding the why some packager use /etc/default/xyz and /etc/xyz/ yet some never use /etc/default .

Any pointers ?

#Deb#package#nFPM
Public
Dr Mircea Zloteanu 🌼🐝

#statstab #304 {MRCV} Methods for Analyzing Multiple Response Categorical Variables (MRCVs)

Thoughts: These are some of the trickier types of data, but maybe not hopeless for analysis.

#mrcv #analysis #r #package #guide #tutorial #categorical

cran.r-project.org/web/package

cran.r-project.orgMRCV: Methods for Analyzing Multiple Response Categorical Variables (MRCVs)Provides functions for analyzing the association between one single response categorical variable (SRCV) and one multiple response categorical variable (MRCV), or between two or three MRCVs. A modified Pearson chi-square statistic can be used to test for marginal independence for the one or two MRCV case, or a more general loglinear modeling approach can be used to examine various other structures of association for the two or three MRCV case. Bootstrap- and asymptotic-based standardized residuals and model-predicted odds ratios are available, in addition to other descriptive information. Statisical methods implemented are described in Bilder et al. (2000) <<a href="https://doi.org/10.1080%2F03610910008813665" target="_top">doi:10.1080/03610910008813665</a>>, Bilder and Loughin (2004) <<a href="https://doi.org/10.1111%2Fj.0006-341X.2004.00147.x" target="_top">doi:10.1111/j.0006-341X.2004.00147.x</a>>, Bilder and Loughin (2007) <<a href="https://doi.org/10.1080%2F03610920600974419" target="_top">doi:10.1080/03610920600974419</a>>, and Koziol and Bilder (2014) <<a href="https://journal.r-project.org/articles/RJ-2014-014/" target="_top">https://journal.r-project.org/articles/RJ-2014-014/</a>>.
ExploreLive feeds
About