Notices tagged with rstats, page 47

Also, that's what Martin Maechler told me and he wrote the code so I trust him on that. I figure that if you have to trust someone to be meticulous and precise then a German-speaking Swiss is a good choice.
-- Douglas Bates
R-help (January 2005) #Rstats

Conquering Caffeinated Amazon Athena with the metis Trio of Packages https://link.rweekly.org/d6n #rstats #datascience

Le Monde puzzle [#1085] https://link.rweekly.org/d6m #rstats #datascience

R Weekly 2019-07 Flipbook, package building https://link.rweekly.org/d6l #rstats #datascience

Frank Harrell: Here is an easy approach that will yield results only slightly less valid than one actually using the response variable:
x <- data.frame(x1, x2, x3, x4, ..., other potential predictors)
x[ , sample(ncol(x))]
Andy Liaw: Hmm... Shouldn't that be something like:
x[, sample(ncol(x), ceiling(ncol(x) * runif(1)))]
-- Frank Harrell and Andy Liaw (about alternative strategies for stepwise regression and 'random parsimony')
R-help (May 2005) #Rstats

Most optimization problems have more than one answer, and the "wrong" ones often seem to be easier to find.
-- John C. Nash (about nonlinear optimization problems)
R-help (April 2013) #Rstats

Query Generation in R https://link.rweekly.org/d6k #rstats #datascience

This is at best a matter of opinion, and credentials do matter for opinions.
-- Brian D. Ripley (in response to the claim that only 1.79e3 is printed with three significant digits whereas 1790 is not)
R-help (December 2006) #Rstats

Post to Mastodon from #Rstats

http://r.iresmi.net/2019/02/15/post-to-mastodon-from-r/

Jeremy Koster: My students were looking at the estimated varying intercepts for each higher-level group (or the "BLUP's", as some people seem to call them).
Douglas Bates: As Alan James once said, "these values are just like the BLUPs - Best Linear Unbiased Predictors - except that they aren't linear and they aren't unbiased and there is no clear sense in which they are "best", but other than that ..."
-- Jeremy Koster and Douglas Bates
R-SIG-Mixed-Models (July 2012) #Rstats

Anatomy of a logistic growth curve https://link.rweekly.org/d6g #rstats #datascience

Brian D. Ripley: Add to package utils in R-devel, after correction. I was surprised you had fallen into the 1:0 trap.
Patrick Burns: I'm surprised too -- good catch.
-- Brian D. Ripley and Patrick Burns (after adding Patrick Burns' head() to the utils package)
R-devel (January 2004) #Rstats

A Shiny app for your perfect circle https://link.rweekly.org/d6f #rstats #datascience

In many cases a) often looks difficult, but on closer inspection turns out to be impossible.
-- Bill Venables (about calculating the negative log-likelihood from a non-independence model)
R-help (April 2008) #Rstats

Using the ropendata R Package to Access Petabytes of Free Internet Telemetry Data from Rapid7 https://link.rweekly.org/d6d #rstats #datascience

PDSwR2 Free Excerpt and New Discount Code https://link.rweekly.org/d6c #rstats #datascience

AI, Machine Learning and Data Science Roundup: February 2019 https://link.rweekly.org/d6b #rstats #datascience

Bert Gunter: However, I do not understand the substitute(...()) idiom. Would you care to explain it? (No is an acceptable answer!).
Bill Dunlap: I don't completely understand it either, I treat it as an idiom. I saw it on this list once.
-- Bert Gunter and Bill Dunlap (on how to recover object names when using the ... argument in a function)
R-help (October 2013) #Rstats

Only with a very high signal to noise ratio (e.g., high true R^2) can torturing data lead to a confession to something other than what the analyst wants to hear.
-- Frank Harrell
R-help (April 2010) #Rstats

What's in a #Mastodon name...
#Rstats
https://mastodon.cloud/media/KTDAWAlBDeGAUobuQkc